• Journal of Korean Society of Forest Science
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• v.99 no.1
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• pp.111-124
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• 2010

This study has intended to develop an evaluation model to select suitable locations of recreation forests in accordance with their types, and to apply the models to the feasibility study of selecting suitable recreation forest locations of candidate sites. To reach this goal, this study employed a Delphi expert survey method and Analytic Hierarchy Process (AHP) for the whole process of model building. And the followings are what this study has found during model building and application process. First, the assessment criteria for classifying recreation forests and selecting suitable locations were initially identified through justification process with two rounds of expert review, after broken down into 2 categories, and then further divided into 6 items and 12 indicators accompanying with hierarchical structure. Second, in the third phase of Delphi expert survey, the relative weights of the assessment criteria were derived by employing AHP. Through overlaying two evaluation categories including resource and usability, 4 types of recreation forest were presented. In the forth phase of the Delphi survey, this study has developed an evaluation model to select suitable locations of recreation forests in accordance with their types using relative weights of the selected indicators through. This study has applied the models to the feasibility study of selecting suitable recreation forest locations of candidate sites, and found that the usability of recreation forest was severely affected by the distance from the capital region, that the closer the locations of natural recreation forests from the capital region, the more advantageous. The developed model can be used to designate recreation forests in accordance with their types.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.365-374
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• 2008

In this paper, we propose a model to enrich an ontology by incrementally extending the relations through variations of patterns. In order to generalize initial patterns, combinations of features are considered as candidate patterns. The candidate patterns are used to extract relations from Wikipedia, which are sorted out according to reliability based on corpus frequency. Selected patterns then are used to extract relations, while extracted relations are again used to extend the patterns of the relation. Through making variations of patterns in incremental enrichment process, the range of pattern selection is broaden and refined, which can increase coverage and accuracy of relations extracted. In the experiments with single-feature based pattern models, we observe that the features of lexical, headword, and hypernym provide reliable information, while POS and syntactic features provide general information that is useful for enrichment of relations. Based on observations on the feature types that are appropriate for each syntactic unit type, we propose a pattern model based on the composition of features as our ongoing work.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.87-94
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• 2005

This paper describes the method of detecting the region of vehicle number plate in colored car image with number plate. Vehicle number plate region generally shows formula colors in accordance with type of car. According to this, we use the method to combine a color ingredient H of HSI color model and a color ingredient Q of YIQ color model. However, the defect which a total operation time takes much exists if it uses such method. Therefore, in this paper, the concurrent accomplishes a candidate area extraction operation as draw a color H and Q ingredient among steps of extracting a region of vehicle number Plate. After the above step, as a next step in combination with color H and Q we can accomplish an region extraction fast by comparing to candidate regions extracted from each steps not to do a comparison operation to all of image pixel information. We also show implementation results Processed at each steps and compare with extraction time according to image resolutions.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.12
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• pp.59-70
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• 2003

Proposed CCRSVP (Candidate Casting RSVP) algorithm is a new fast handoff method which uses advanced multicasting method and RSVP for IEEE 802.11 Wireless LAN (WLAN) environments. The proposed algorithm shows good performance in the handoff latency and the B/W efficiency aspect and guarantees QoS because it uses L2 information (BSSID) of WLAN and starts to reserve resources and multicast packets before L2 handoff completes. We also propose a Markov chain performance analysis model in which we can analyze the handoff performance of various handoff algorithms. Using the model, we compare bandwidth efficiency of the proposed algorithm with existing handoff algorithms which use RSVP by analyzing blocking probability of session, resource usage, and the average number of ongoing session in a cell. The results show that the proposed algorithm shows better performance than the existing algorithms in the above three performance aspects.

• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.215-231
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• 2017

The US presidential primaries take place sequentially in different places with a time lag. However, they have not attracted as much attention in terms of modelling as the US presidential election has. This study applied several autologistic models to find the relation between the outcome of the primary election for a Democrat candidate with socioeconomic attributes in consideration of spatial and temporal dependence. According to the result applied to the 2016 election data at the county level, Hillary Clinton was supported by people in counties with high population rates of old age, Black, female and Hispanic. In addition, spatial dependence was observed, representing that people were likely to support the same candidate who was supported from neighboring counties. Positive auto-correlation was also observed in the time-series of the election outcome. Among several autologistic models of this study, the model specifying the effect of Super Tuesday had the best fit.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.297-310
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• 2013

In this paper, we present a model-based video bit rate estimation scheme for reducing the bit rate while maintaining a subjective quality in many video streaming services limited by network bandwidth, such as IPTV services. First, we extract major parameters which serve as an indirect measurement of frame's bits. Using those parameters, the proposed bit rate estimation scheme can extract candidate frames. Finally, the bit rate of each segment is estimated by statistical analysis and a mathematical model based on a given target quality. In experimental results, we show that the proposed scheme can reduce the bit rate on average by 43% in low-complexity video while maintaining the subjective quality. To find the appropriate bit rate based on video contents, the proposed schemes can estimate the bit rate with neither the repeated full encoding nor subjective quality test. On average, the bit rate can be automatically estimated by encoding the candidate frames of 4%.

• Journal of the military operations research society of Korea
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• v.34 no.2
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• pp.63-77
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• 2008

With the limited frequency spectrum and an increasing demand for cellular communication services, the problem of channel assignment becomes increasingly important. However, finding a conflict free channel assignment with the minimum channel span is NP hard. The innovations are cellular concept, dynamic channel assignment and hierarchical network design. We consider the frequency assignment problem and the base station placement simultaneously. Our model takes the candidate locations emanating from this process and the cost of assigning a frequency, operating and maintaining equipment as an input. Hierarchical network design using genetic algorithm is the first three-tier (Macro, Micro, Pico) model. We increase the reality through applying to Electromagnetic Compatibility Constraints. Computational experiments on 72 problem instances which have $15{\sim}40$ candidate locations demonstrate the computational viability of our procedure. The result of experiments increases the reality and covers 90% of the demand.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.6
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• pp.15-24
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• 2011

As increase awareness of intelligent vehicle systems, many kinds of lane detection algorithm have been proposed. General boundary extraction method can bring good result in detection of lane on the road. But a shadow on the road, or other boundaries, such as horizontal lines can be detected. The method using morphological operations was used to extract information about Lane. By applying HSV color model for color information of lane, the candidate of the lane can be extracted. In this paper, the lane detection region was set by Hough transformation using the candidate of the lane. By extracting lane markings on the lane detection region, lane detection method can bring good result.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.79-86
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• 2009

This study proposed a method of detecting the facial area by calculating Euclidian distances among skin color elements and extracting the characteristics of the face. The proposed algorithm is composed of light calibration and face detection. The light calibration process performs calibration for the change of light. The face detection process extracts the area of skin color by calculating Euclidian distances to the input images using as characteristic vectors color and chroma in 20 skin color sample images. From the extracted facial area candidate, the eyes were detected in space C of color model CMY, and the mouth was detected in space Q of color model YIQ. From the extracted facial area candidate, the facial area was detected based on the knowledge of an ordinary face. When an experiment was conducted with 40 color images of face as input images, the method showed a face detection rate of 100%.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.1-11
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• 2021

This paper presents a procedure to extract lane line models using a set of proposed methods. Firstly, an image warping method based on homography is proposed to transform a target image into an image which is efficient to find lane pixels within a certain region in the image. Secondly, a method to use the combination of the results of edge detection and HSL (Hue, Saturation, and Lightness) transform is proposed to detect lane candidate pixels with reliability. Thirdly, erroneous candidate lane pixels are eliminated using a selection area method. Fourthly, a method to fit lane pixels to quadratic polynomials is proposed. In order to test the validity of the proposed procedure, a set of black-box images captured under varying illumination and noise conditions were used. The experimental results show that the proposed procedure could overcome the problems of color-only and edge-only based methods and extract lane pixels and model the lane line geometry effectively within less than 0.6 seconds per frame under a low-cost computing environment.