• Progress in Medical Physics
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• v.7 no.1
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• pp.53-64
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• 1996

Purpose: The purposes of this paper are to develop a theoretical basis that the beam directions should be considered when the mechanical accuracy of teletherapy machine is evaluated by the star pattern test, to develop methods using asymmetric field in length to simulate beam direction for the case that beam direction does not appear on film. Method: In evaluating mechanical rotational accuracy of the gantry of teletherapy unit by the star pattern test, the direction of radiation beams was considered. A star pattern using some narrow beams was made. Density profiles at 10cm far from estimated gantry axis on the star pattern were measured using an optical densitometer. On each profile, one coordimate of a beam axis was determined. A pair of coordinates on a beam axis form an equation of the axis. Assume that a unit vector equation omitted is with same direction as radiation beam and a vector equation omitted is a vector directing to the beam axis from the estimated gantry axis. Then, a vector product equation omitted ${\times}$ equation omitted is an area vector of which the absolute value is equal to the distance from the estimated gantry axis to the beam axis. The coordinate of gantry axis was obtained by using least-square method for the area vectors relative to the average of whole area vectors. For the axis, the maximum of absolute value of area vectors would be an accuracy of the gantry rotation axis. For the evaluation of mechanical accuracies of collimator and couch axes for which beam direction could not be depicted on a star pattern test film, narrow beams asymmetric in field length was used to simulate beam direction. Result: For a star test pattern to evaluate the mechanical accuracy of rotational axes of a telectherapy machine, the result considering beam direction was different from that ignoring beam direction. For the evaluation of mechanical accuracies of collimator and couch axes by means of a star pattern test, narrow asymmetric beams could simulate beam direction. Conclusion: When a star pattern test is used to evaluate the mechanical accuracy of a teletherapy unit, beam direction must be considered or simulated, and quantitatively evaluated.

• Journal of The Korean Astronomical Society
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• v.35 no.4
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• pp.209-220
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• 2002

In order to increase the completeness of the investigations of stellar abundances, we can use spectrum synthesis method, new atomic data and observation of stellar spectra with resolution comparable to solar spectral atlases. We made a brief review of main problems of these three ways. We present new results of abundance determinations in the atmospheres of four stars. The first is the implementation of new atomic data to well known Przybylski's star. We show that the number of spectral lines, which can be identificated in the spectrum of this star, can be significantly higher. The second example is the investigation of $\zeta$ Cyg. We found the abundances of 51 elements in the atmosphere of this mild barium star. The third example is halo star HD221170. Our preliminary abundance pattern consists of 42 elements. The heaviest elements in this pattern are U and Th. The last star is the spectroscopic binary HD153720. The number of elements investigated in the spectra of components of this star is not large, but the results show that the components are Am-stars.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.36.1-37
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• 2021

Six images of IRC+10216 taken by the Hubble Space Telescope at three epochs in 2001, 2011, and 2016 are compared in the rest frame of the central carbon star. An accurate astrometry has been achieved with the help of Gaia Data Release 2. The positions of the carbon star in the individual epochs are determined using its known proper motion, defining the rest frame of the star. In 2016, a local brightness peak with compact and red nature is detected at the stellar position. A comparison of the color maps between 2016 and 2011 epochs reveals that the reddest spot moved along with the star, suggesting a possibility of its being the dusty material surrounding the carbon star. Relatively red, ambient region is distributed in an Ω shape and well corresponds to the dusty disk previously suggested based on near-infrared polarization observations. In a larger scale, differential proper motion of multiple ring-like pattern in the rest frame of the star is used to derive the average expansion velocity of transverse wind components, resulting in ~12.5 km s-1 (d/123 pc), where d is the distance to IRC+10216. Three dimensional geometry is implied from its comparison with the line-of-sight wind velocity determined from half-widths of submillimeter emission line profiles of abundant molecules. Uneven temporal variations in brightness for different searchlight beams and anisotropic distribution of extended halo are revisited in the context of the stellar light illumination through a porous envelope with postulated longer-term variations for a period of 10 years.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.454-457
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• 2005

Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist prolific patterns and/or long patterns. And calendar based on temporal association rules proposes the discovery of association rules along with their temporal patterns in terms of calendar schemas, but this approach is also adopt an Apriori-like candidate set generation. In this paper, we propose an efficient temporal frequent pattern mining using TFP-tree (Temporal Frequent Pattern tree). This approach has three advantages: (1) this method separates many partitions by according to maximum size domain and only scans the transaction once for reducing the I/O cost. (2) This method maintains all of transactions using FP-trees. (3) We only have the FP-trees of I-star pattern and other star pattern nodes only link them step by step for efficient mining and the saving memory. Our performance study shows that the TFP-tree is efficient and scalable for mining, and is about an order of magnitude faster than the Apriori algorithm and also faster than calendar based on temporal frequent pattern mining methods.

• Proceedings of the Korean Society of Radiological Science
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• 1994.10a
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• pp.98.1-98.1
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• 1994

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5477-5485
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• 2011

This study comparatively analyzed the instrumentation and the voicing structure, which were shown in the film music titled "Star Wars-Main Title" by John Williams(1932~), with analytical technique that the writer mapped out, and aimed to discover the progression principle in orchestration based on the results. Also, it applied a functional part-division method that was classified and distributed into 3 functional parts according to auditory cognitive level as for each of functional elements such as the musical element. And, it made it pattern for the vertical structure and the voicing structure in musical instruments, which were distributed to each functional part based on this, and comparatively analyzed the standard point in a change which were shown according to progression of music, namely, the operating technique. As for the results of this study, first, each theme has specific instrumentation pattern. Unity was emphasized by consistently organizing those things in exposition, reprise, and recapitulation of each theme. To reinforce diversity, an attempt was made such as adding and reducing auxiliary instruments in the middle part and the rear part. Second, even in a change of instrumentation pattern by passage in accordance with a change in theme amid each part, the same instrumental group was organized in the middle part, thereby having maintained unity. Third, to strengthen diversity by clause, which is forming each theme, a continuous change in voicing pattern was created by adding or omitting a part. Fourth, the voicing concentration was maintained the structure of "thinness-thickness" in the whole musical piece. However, in part 2 that is repeated theme 3, diversity was pursued with a unique change of "thickness-thickness." Fifth, in part 4 that is indicated theme 4, the other diversity was intensified with the inverted range in the front part and the middle part. Accordingly, based on the conclusions that were indicated in this work, it is desired to be conducive to understanding the horizontal consideration and the progression principle of orchestration.

• Journal of radiological science and technology
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• v.30 no.4
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• pp.419-426
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• 2007

In this paper, the input pattern vectors are extracted and the learning algorithms is designed to recognize taste(bitter, sweet, sour and salty) pattern vectors. The signal intensity of taste are used to compose the input pattern vectors. The SOM(Self Organizing Maps) algorithm for taste pattern recognition is used to learn initial reference vectors and the ot-star learning algorithm is used to determine the class of the output neurons of the sunclass layer. The weights of the proposed algorithm which is between the input layer and the subclass layer can be learned to determine initial reference vectors by using SOM algorithm and to learn reference vectors by using LVQ(Learning Vector Quantization) algorithm. The pattern vectors are classified into subclasses by neurons in the subclass layer, and the weights between subclass layer and output layer are learned to classify the classified subclass, which is enclosed a class. To classify the pattern vectors, the proposed algorithm is simulated with ones of the conventional LVQ, and it is confirmed that the proposed learning method is more successful classification than the conventional LVQ.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.95-103
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• 2006

In this paper, the input pattern vectors are extracted and the learning algorithms is designed to recognize EEG pattern vectors. The frequency and amplitude of alpha rhythms and beta rhythms are used to compose the input pattern vectors. And the algorithm for EEG pattern recognition is used SOM to learn initial reference vectors and out-star learning algorithm to determine the class of the output neurons of the subclass layer. The weights of the proposed algorithm which is between the input layer and the subclass layer can be learned to determine initial reference vectors by using SOM algorithm and to learn reference vectors by using LVQ algorithm, and pattern vectors is classified into subclasses by neurons which is being in the subclass layer, and the weights between subclass layer and output layer is learned to classify the classified subclass, which is enclosed a class. To classify the pattern vectors of EEG, the proposed algorithm is simulated with ones of the conventional LVQ, and it was a confirmation that the proposed learning method is more successful classification than the conventional LVQ.

• BMB Reports
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• v.41 no.1
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• pp.23-28
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• 2008

The altered amino acid (AA) levels as neurotransmitter closely correlate to neurodegenerative conditions including Alzheimer's disease (AD). Target profiling analysis of nineteen AAs in brain cortex samples from three Tg2576 mice as AD model and three littermate mice as control model was achieved as their N(O,S)-ethoxycarbonyl/tert-butyldimethylsilyl derivatives by gas chromatography. Subsequently, star pattern recognition analysis was performed on the brain AA levels of AD mice after normalization to the corresponding control median values. As compared to control mice, $\gamma$-aminobutyric acid among ten AAs found in brain samples was significantly reduced (P < 0.01) while leucine was significantly elevated (P < 0.02) in AD mice. The normalized AA levels of the three AD mice were transformed into distorted star patterns which was different from the decagonal shape of control median. The present method allowed visual discrimination of the three AD mice from the controls based on the ten normalized AA levels.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.77-86
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• 2005

In this paper, we designed a learning algorithm of LVQ that extracts classification errors and learns ones and improves classification performance. The proposed LVQ learning algorithm is the learning Networks which is use SOM to learn initial reference vectors and out-star learning algorithm to determine the class of the output neurons of LVQ. To extract pattern vectors which cause classification errors, we proposed the error-cause condition, which uses that condition and constructed the pattern vector space which consists of the input pattern vectors that cause the classification errors and learned these pattern vectors , and improved performance of the pattern classification. To prove the performance of the proposed learning algorithm, the simulation is performed by using training vectors and test vectors that are Fisher' Iris data and EMG data, and classification performance of the proposed learning method is compared with ones of the conventional LVQ, and it was a confirmation that the proposed learning method is more successful classification than the conventional classification.