• 대한핵의학회:학술대회논문집
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• 2002.05a
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• pp.25-27
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• 2002

With the advent of multidetector-row CT, lung cancer imaging is much more promising than before. However, the effectiveness of multidetector-row CT in making an initial diagnosis, staging, and evaluating post-treatment changes of lung cancer still remains to be proved. Fast imaging along with volumetric data set and attendant multi-planar imaging provide much more details on the anatomic changes and pathology associated with lung cancer. However, with images showing anatomic and pathologic changes only, radiologists confront with several questions the answers of which may help evaluate lung cancer more thoroughly. The frequent questions that I have in dally practice of chest CT interpretation are as follows.

• Journal of information and communication convergence engineering
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• v.1 no.1
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• pp.53-57
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• 2003

Chaos theory is a study researching the irregular, unpredictable behavior of deterministic and non-linear dynamical system. The interpretation using Chaos makes us evaluate characteristic existing in status space of system by tine series, so that the extraction of Chaos characteristic understanding and those characteristics enables us to do high precision interpretation. Therefore, This paper propose the new method which is adopted in extracting character features and recognizing characters using the Chaos Theory. Firstly, it gets features of mesh feature, projection feature and cross distance feature from input character images. And their feature is converted into time series data. Then using the modified Henon system suggested in this paper, it gets last features of character image after calculating Box-counting dimension, Natural Measure, information bit and information dimension which are meant fractal dimension. Finally, character recognition is performed by statistically finding out the each information bit showing the minimum difference against the normalized pattern database. An experimental result shows 99% character classification rates for 2,350 Korean characters (Hangul) using proposed method in this paper.

• Journal of Korean Society of Forest Science
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• v.96 no.3
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• pp.251-258
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• 2007

Airborne Lidar (light detection and ranging) can be an effective alternative in forest inventory to overcome the limitations of conventional field survey and aerial photo interpretation. In this study, we attempt to develop methodologies to identify individual trees and to estimate tree height from airborne Lidar data. Initially, digital elevation model (DEM) data representing the exact ground surface were generated by removing non-ground returns from the multiple-return laser point clouds, obtained over the coniferous forest site of rugged terrain. Based on the canopy height model (CHM) data representing non-ground layer, individual tree heights are extracted through pseudo-grid method and moving window filtering algorithm. Comparing with field survey data and aerial photo interpretation on sample plots, the number of trees extracted from Lidar data show over 90% accuracy and tree heights were underestimated within 1.1m in average at two plantation stands of pine (Pinus koraiensis) and larch (Larix leptolepis).

• Annals of Clinical Neurophysiology
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• v.1 no.1
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• pp.39-46
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• 1999

Transcranial doppler ultrasonography (TCD) is a new, non-invasive and easily applicable method to evaluate cerebral hemodynamics. Last 10 years, its use in Korea has been dramatically expanded, but the qualification of TCD laboratory has yet to be settled. Since duplex sonography is seldom used in Korea, we have to depend totally on TCD to evaluate cerebral hemodynamic changes. Thus, all of the available data from every detectabler cerebral arteries has to be obtained for accurate interpretation of TCD measurements. Moreover, flow direction and wave form should be concerned in addition to the flow velocity. In this article, I present technique to measure the anterior, meddle and posterior cerebral arteries, the internal carotid artery siphon and at cervical level, and the vertebral and the basilar artery, and normal values for these measurements which is essential for the adequate interpretation.

• Language and Information
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• v.6 no.2
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• pp.153-169
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• 2002

In this paper I develop a mechanism of interpreting Korean “wh-phrases”. The phrases have various readings depending on where they occur and they could be ambiguous even in the same structure. Yet their readings are subject to certain restrictions. I assume that the “wh-phrases” behave like variables and that there are three quantifiers to bind the phrases; $COMP_{wh},\;COMP_{conc}$ and derivational $\exists$-quantifier. Based on the assumptions I suggest derivational quantification, which consists of three conditions. 1) A quantifier can bind only when it merges into the derivation; 2) $\exists$-quantifier accompanies 〔-OP〕 complementizer but its activation is optional; 3) an instance of quantification makes the clause opaque to other instances of quantification. Scrambling data support derivational approach and across-the-board interpretation motivates the opacity condition. The opacity condition accounts for ATB- interpretations of reflexive pronouns. It can also explain the island effect of wh-islands without adopting covert wh-movement in Korean.

• ETRI Journal
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• v.34 no.5
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• pp.743-752
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• 2012

Semantic interpretation of the relationship between noun compound (NC) elements has been a challenging issue due to the lack of contextual information, the unbounded number of combinations, and the absence of a universally accepted system for the categorization. The current models require a huge corpus of data to extract contextual information, which limits their usage in many situations. In this paper, a new semantic relations interpreter for NCs based on novel lightweight binary features is proposed. Some of the binary features used are novel. In addition, the interpreter uses a new feature selection method. By developing these new features and techniques, the proposed method removes the need for any huge corpuses. Implementing this method using a modular and plugin-based framework, and by training it using the largest and the most current fine-grained data set, shows that the accuracy is better than that of previously reported upon methods that utilize large corpuses. This improvement in accuracy and the provision of superior efficiency is achieved not only by improving the old features with such techniques as semantic scattering and sense collocation, but also by using various novel features and classifier max entropy. That the accuracy of the max entropy classifier is higher compared to that of other classifiers, such as a support vector machine, a Na$\ddot{i}$ve Bayes, and a decision tree, is also shown.

• Natural Product Sciences
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• v.14 no.3
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• pp.177-181
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• 2008

Five polyacetylenes, ginsenoyne K (1), (Z)-1-methoxyheptadeca-9-en-4,6-diyne-3-one (2), panaxydol (3), panaxydiol (4), and (E)-heptadeca-8-en-4,6-diyne-3,10-diol (5) were isolated from the adventitious roots of Panax ginseng and their chemical structurFive polyacetylenes, ginsenoyne K (1), (Z)-1-methoxyheptadeca-9-en-4,6-diyne-3-one (2), panaxydol (3), panaxydiol (4), and (E)-heptadeca-8-en-4,6-diyne-3,10-diol (5) were isolated from the adventitious roots of Panax ginseng and their chemical structures were elucidated by interpretation of spectroscopic data. Among the isolated compounds, compounds 2 and 5 were reported for the first time as a natural product. Ginsenoyne K (1) showed dose-dependent inhibitory effect on dopa oxidase activity of tyrosinase.es were elucidated by interpretation of spectroscopic data. Among the isolated compounds, compounds 2 and 5 were reported for the first time as a natural product. Ginsenoyne K (1) showed dose-dependent inhibitory effect on dopa oxidase activity of tyrosinase.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.196-199
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• 2008

Lineament is defined generally as a linear feature or pattern on interpretation of a satellite image and indicates the geological structures such as faults and fractures. For this reason, a lineament extraction and analysis using remote sensing images have been widely used for mapping large areas. The Gyeong-gang Fault is a NNE trending structure located in Gangwon-do and Kyeonggi-do district. However, a few geological researches on that fault have been carried out and its trace or continuity is ambiguous. In this study, we investigate the geologic features at Gyeong-gang Fault Zone using LANDSAT ETM+ satellite image and SRTM digital elevation model. In order to extract the characteristics of geologic features effectively, we transform the LANDSAT ETM+ image using Principal Component Analysis (PCA) and create a shade relief from SRTM data with various illumination angles. The results show that it is possible to identify the dimensions and orientations of the geologic features at Gyeong-gang Fault Zone using remote sensing data. An aerial photograph interpretation and a field work will be future tasks for more accurate analysis in this area.

• School Mathematics
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• v.3 no.2
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• pp.281-294
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• 2001

As a measure of the center of data, arithmetical mean, median, mode, harmonic mean and geometric mean are generally used. Students must learn qualitative aspect of average values as well as its calculation for its adequate use. As the result of the learning, they should be able to select the appropriate average value according to the characteristic of data and problem context. For this object, the historical origin and visual interpretation of average values were introduced in this paper. And to help teaching several meanings of average values, several examples including context were suggested.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.73-81
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• 2000

The variance inflation factor can be expressed by the square of the ratio of t-statistics associated with slopes of partial regression and partial residual plots. Disagreement of two sides in the interpretation can be occurred, and we analyze it with some illustrations.