• Journal of Biomedical Engineering Research
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• v.31 no.3
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• pp.227-233
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• 2010

This study analyzed performance according to kick point and stiffness of Soft-$golf^{TM}$ shaft. This research team developed soft-$golf^{TM}$ as a new fusion sports with similar motions with golf and it can be learned safely for all age groups in 2002. The head of Soft-$golf^{TM}$ club is made of zinc alloy and has a mesh or a grid structure, and shaft uses carbon graphite to reduce the total weight of the club. To improve carry distance and to assure consistency of a ball during Soft-$golf^{TM}$ swing, this study manufactured shaft with various kick points (low, middle and high) and stiffness (stiff, regular, lady, morelady) and analyzed a swing motion with characteristics of each shaft presented in a dynamic condition such as a ball's speed, a head's torsion angle and a ball's deviation with ProAnalyst program through a high-speed camera taking pictures using a swing machine robot system(Robo-7). From all of the results, this study determined an appropriate shaft of Soft-$golf^{TM}$.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.14-22
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• 2001

Off-line handwritten numeral recognition is a very difficult task and hard to achieve high recognition results using a single feature and a single classifier, since handwritten numerals contain many pattern variations which mostly depend upon individual writing styles. In this paper, we propose handwritten numeral recognition system using hybrid features and combined classifier. To improve recognition rate, we select mutually helpful features -directional features, crossing point feature and mesh features- and make throe new hybrid feature sets by using these features. These hybrid feature sets hold the local and global characteristics of input numeral images. And we implement combined classifier by combining three neural network classifiers to achieve high recognition rate, where fuzzy integral is used for multiple network fusion. In order to verify the performance of the proposed recognition system, experiments with the unconstrained handwritten numeral database of Concordia University, Canada were performed. As a result, our method has produced 97.85% of the recognition rate.

• Journal of the Korean Chemical Society
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• v.13 no.1
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• pp.49-55
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• 1969

X-ray Fluorescence Spectrographic method has been applied for the rapid determination of main components, such as $SiO_2$, $Al_2O_3$, $Fe_2O_3$, CaO, MgO and $K_2O$ in Silicate Minerals. In this method, Boric Acid was used as a binder after fusion with Lithium Tetraborate in the briquet-making process. The Lithium Flubride, Ammonium di-Hydrogen Phosphate and Ethylene Diamine d-Tartrate crystals were used with Scintillation counter and Gas Flow counter as the detectors. Several influences on this method were discussed, including the particle size of samples and reducing of the matrix effects by dilution with Boric Acid and addition of Lanthanum Oxide with the diluent. In order to test the reproducibility of this method described above, the determination of the same kind of samples were carried out repeatedly, and the results obtained were presented in the table. Calibration curves for each element were presented, and the application of the method was tested with International Rock Standard T-Ⅰ. All the results obtained by X-Ray Fluorescence Spectrographic method were compared with the results by conventional chemical method.