• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.375-382
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• 2002

Handwritten character recognition is classified into on-line handwritten character recognition and off-line handwritten character recognition. On-line handwritten character recognition has made a remarkable outcome compared to off-line hacdwritten character recognition. This method can acquire the dynamic written information such as the writing order and the position of a stroke by means of pen-based electronic input device such as a tablet board. On the contrary, Any dynamic information can not be acquired in off-line handwritten character recognition since there are extreme overlapping between consonants and vowels, and heavily noisy images between strokes, which change the recognition performance with the result of the preprocessing. This paper proposes a method that effectively extracts the stroke including dynamic information of characters for off-line Korean handwritten character recognition. First of all, this method makes improvement and binarization of input handwritten character image as preprocessing procedure using watershed algorithm. The next procedure is extraction of skeleton by using the transformed Lu and Wang's thinning: algorithm, and segment pixel array is extracted by abstracting the feature point of the characters. Then, the vectorization is executed with a maximum permission error method. In the case that a few strokes are bound in a segment, a segment pixel array is divided with two or more segment vectors. In order to reconstruct the extracted segment vector with a complete stroke, the directional component of the vector is mortified by using right-hand writing coordinate system. With combination of segment vectors which are adjacent and can be combined, the reconstruction of complete stroke is made out which is suitable for character recognition. As experimentation, it is verified that the proposed method is suitable for handwritten Korean character recognition.

• Analytical Science and Technology
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• v.7 no.3
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• pp.339-347
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• 1994

A multicolumn system consisted of two valve(10-port and 6-port valve)-three column (28% DC 200, SP 1700 and Chromosorb 102 column) was developed. Nine natural gas components composed of $N_2$, $CH_4$, $CO_2$, $C_2H_6$, $C_3H_8$, $i-C_4H_{10}$, $n-C_4H_{10}$, $i-C_5H_{12}$ 및 $n-C_5H_{12}$ completed all the baseline separation within 18 minutes. The accuracy and the precision of this system was tested. The retention times and the peak areas were determined with a repeatability between 0.02 and 0.16%, and less than 1%, respectively. Calibration curves for natural-gas components were plotted by the partial pressure injection method of pure gases, and good linear relationships for each component were presented. By using these calibration curves the accuracy of the multicolumn system compaired with that of the single column system for a certified standard gas of natural gas. As a result, relative error in the single and the multicolumn system was less than 0.5% and 0.04%, respectively. The result of application of this system in the analysis of importing LNG composition showed that the heating values calculated by the multicolum system were estimated lower compared with those calculated by the single column system and consequently, the importing price of LNG was able to be cut down.

• Journal of Bio-Environment Control
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• v.4 no.1
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• pp.50-58
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• 1995

These studies were carried out to develop a system for non -destructive and continuous measurement of fresh weight and to analyse the growth response of leaf lettuce under the different nutrient solution and light condition with this system. The developed measurement system was consisted of four load cells and a microcomputer. The output from the system was highly positive correlation with the plant fresh weight above the surface of the hydroponic solution. The top fresh weight of plant could be measured within the error $\pm$ 1.0g in the range of 0 - 2000g. The top fresh weight of leaf lettuce increased 44 times at 18th day after transferring to the nutrient solution, and the maximum growth rate was observed at 13th day after transferring. The growth rate was 10.7- 29.6% per day during 18 days. Optimum concentration of the nutrient solution for the growth of lettuce was 1.4 - 2.2 mS/cm of EC level. When the light condition was changed from dark to light, the fresh weight was temporarily decreased, but the fresh weight increased under the opposite condition. Top fresh weight of leaf lettuce in the darkness normally increased within 12 hours after darkness treatment, and then slowly increased until 78 hours under continuous dark condition. After that times, the fresh weight began to decrease.

• The Korean Journal of Nuclear Medicine Technology
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• v.12 no.3
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• pp.222-228
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• 2008

Purpose: The objectives of this study were to compare the left ventricle ejection fraction (LVEF) from gated cardiac blood pool scan (GCBP) for analysis auto-drawing region of interest mode (AROI) and manual-drawing region of interest mode (MROI), respectively. To evaluation the relationships between values produced by both ROI modes. Materials and Methods: Gated cardiac blood pool scan using in vivo method Tc-99m Red Blood Cell were performed for 33 patients (mean age: $53.2{\pm}13.2\;y$) with objective of chemotherapy using single head gamma camera (ADAC Laboratories, Milpitas, CA). Left ventricular ejection fraction was automatically and manually measured, respectively. Results: There was significant difference statistically between AROI and MROI ($LVEF^{AROI}$: $71.4{\pm}12.4%$ vs. $LVEF^{MROI}$: $65.8{\pm}5.9%$, p=0.003). Intra-observer agreements in AROI was higher than MROI ($\gamma^{AROI}=0.964$, Cronbach's $\alpha^{AROI}=0.986$ vs. $\gamma^{MROI}=0.793$, Cronbach's $\alpha^{MROI}=0.911$), either. Additionally, there was no significant difference statistically at best septal view (${\Delta}LVEF^{BSV}=0.7{\pm}2.3%$, p=0.233), however statistically significant difference was found at badly separated septal view (${\Delta}LVEF=10.9{\pm}11.4%$, p=0.001). Moreover, Intra-observer agreements in best septal view was higher than badly separated septal view ($\gamma^{BSV}=0.939$, Cronbach's $\alpha^{BSV}=0.978$; $\gamma=0.948$, Cronbach's $\alpha=0.981$ at AROI, $\gamma^{BSV}=0.836$, Cronbach's $\alpha^{BSV}=0.936$; $\gamma=0.748$, Cronbach's $\alpha=0.888$ at MROI). Conclusion: When best septal view was acquired, LVEF by AROI and MROI indicated not different. Comparing Intra-observer agreements with AROI and MROI, the AROI tended to show higher. Therefore, it is considered that the AROI than MROI is valuable in reproducibility and objective when ROI analysis by acquire left ventricular of best septal view.