• Journal of Chest Surgery
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• v.23 no.3
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• pp.438-451
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• 1990

Pneumatic total artificial heart[TAH] has been clinically applied for the purpose of permanent or temporary use followed by cardiac transplantation in the patients with end stage heart diseases. In spite of the good durability of the pneumatic TAH, thrombus formation, bleeding and infection resulted in death. The Tomasu heart, which is a type of pneumatic TAH, was used in this study. This model is a modified Jarvik heart and consists of atrial cuffs, outflow vascular grafts and thin-layer seamless diaphragm type of ventricles. Cardiac outputs of the left artificial heart were measured by Donovan`s mock circulation under variable conditions of driving parameters, and an experimental artificial heart implantation was performed in 4 calves to observe the changes of hemodynamic parameters in early postoperative period and hematologic and bio-chemical changes in a long-term survival case. In the mock circulation test, cardiac output of the heart was increased with the increase of the left atrial pressure and left driving pressure. Maximum cardiac output was obtained at the heart rate of 120 to 130/min and percent systole of 40 to 45Zo under the condition of a constant left driving pressure of 180mmHg and left atrial pressure of 10mmHg. During the first 24 hours of TAH pumping, driving pressure ranged from 178$\pm$5mmHg to 187$\pm$8mmHg for the left heart and from 58$\pm$6mmHg to 78$\pm$28mmHg for the right heart. The Mean arterial pressure significantly increased between 2 and 8 hours after the start of pumping. The survival time ranged from 27 hours to 46 days. The causes of death were respiratory failure in 2 cases, mechanical valve failure in one, and left ventricular outflow obstruction due to thrombus in a 46-day survival case. This study demonstrated that Tomasu artificial heart operated effectively during the first 24 hours of artificial heart pumping, but thrombus formation around the valve holding area was the main problem in long-term survival case.

• Journal of Sensor Science and Technology
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• v.31 no.6
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• pp.411-417
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• 2022

In this paper, we propose a sensor with a C-shaped load cell to detect force change when a person sitting on the chair in an electrical transport-convenience vehicle is pushing ground by both heels. The load cell built in the vehicle is mechanically deformed by the vertical force owing to the human weight and the horizontal force by ground-pushing feet. The deformation rate of the load cell and its distribution are simulated using finite element analysis. In the simulation, the applied loads are preset in the range of 10 kg - 100 kg with a step size of 10 kg, and the ground-pushing force by feet is increased to 40 N with a step size of 5 N with respect to each applied load level. The resistance change of the load cell was observed to be linear in simulation as well as in measurement. the maximum difference between simulation and measurement was 0.89 % when the strain gauge constant was 2.243. The constant has a large influence on the difference. The proposed sensor was fabricated by connecting an instrument amplifier and a microcontroller to a load cell and used to detect the force by ground-pushing feet. To detect foot driving, the reference signal was set to 130% of the load, and the duration of the sensor output signal exceeding the reference signal was set to 0.6 s. In a test of a vehicle built with the proposed sensor, the footpushing force by the worker could be successfully detected even when the worker was working.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1633-1641
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• 2020

Objective: The objective of this study was to develop a model for estimating the carcass weight of Hanwoo cattle as a function of body measurements using three different modeling approaches: i) multiple regression analysis, ii) partial least square regression analysis, and iii) a neural network. Methods: Data from a total of 134 Hanwoo cattle were obtained from the National Institute of Animal Science in South Korea. Among the 372 variables in the raw data, 20 variables related to carcass weight and body measurements were extracted to use in multiple regression, partial least square regression, and an artificial neural network to estimate the cold carcass weight of Hanwoo cattle by any of seven body measurements significantly related to carcass weight or by all 19 body measurement variables. For developing and training the model, 100 data points were used, whereas the 34 remaining data points were used to test the model estimation. Results: The R² values from testing the developed models by multiple regression, partial least square regression, and an artificial neural network with seven significant variables were 0.91, 0.91, and 0.92, respectively, whereas all the methods exhibited similar R² values of approximately 0.93 with all 19 body measurement variables. In addition, relative errors were within 4%, suggesting that the developed model was reliable in estimating Hanwoo cattle carcass weight. The neural network exhibited the highest accuracy. Conclusion: The developed model was applicable for estimating Hanwoo cattle carcass weight using body measurements. Because the procedure and required variables could differ according to the type of model, it was necessary to select the best model suitable for the system with which to calculate the model.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.6
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• pp.884-892
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• 2014

The purpose of this study was to investigate the drying characteristics and drying models of Ainsliaea acerifolia Sch. Bip. using far-infrared thin layer drying. Far-infrared thin layer drying test on Ainsliaea acerifolia Sch. Bip. was conducted at two air velocities of 0.6 and 0.8 m/sec, as well as three drying temperatures of 40, 45, and $50^{\circ}C$ respectively. The drying models were estimated using coefficient of determination and root mean square error. Drying characteristics were analyzed based on factors such as drying rate, leaf color changes, antioxidant activity, and contents of polyphenolics and flavonoids. The results revealed that increases in drying temperature and air velocity caused a reduction in drying time. The Thompson model was considered suitable for thin layer drying using far-infrared radiation for Ainsliaea accerifolia Sch. Bip. Greenness and yellowness values decreased and lightness values increased after far-infrared thin layer drying, and the color difference (${\Delta}E$) values at $40^{\circ}C$ were higher than those at $45^{\circ}C$ and $50^{\circ}C$. The antioxidant properties of Ainsliaea acerifolia Sch. Bip. decreased under all far-infrared thin layer drying conditions, and the highest polyphenolic content (37.9 mg/g), flavonoid content (22.7 mg/g), DPPH radical scavenging activity (32.5), and ABTS radical scavenging activity (31.1) were observed at a drying temperature of $40^{\circ}C$ with an air velocity of 0.8 m/sec.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.15-33
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• 2021

In this study, the possibility of discriminating Fire blight (FB) infection tested using the hyperspectral imagery. The reflectance of healthy and infected leaves and branches was acquired with 5 nm of full width at high maximum (FWHM) and then it was standardized to 10 nm, 25 nm, 50 nm, and 80 nm of FWHM. The standardized samples were divided into training and test sets at ratios of 7:3, 5:5 and 3:7 to find the optimal bands of FWHM by the decision tree analysis. Classification accuracy was evaluated using overall accuracy (OA) and kappa coefficient (KC). The hyperspectral reflectance of infected leaves and branches was significantly lower than those of healthy green, red-edge (RE) and near infrared (NIR) regions. The bands selected for the first node were generally 750 and 800 nm; these were used to identify the infection of leaves and branches, respectively. The accuracy of the classifier was higher in the 7:3 ratio. Four bands with 50 nm of FWHM (450, 650, 750, and 950 nm) might be reasonable because the difference in the recalculated accuracy between 8 bands with 10 nm of FWHM (440, 580, 640, 660, 680, 710, 730, and 740 nm) and 4 bands was only 1.8% for OA and 4.1% for KC, respectively. Finally, adding two bands (550 nm and 800 nm with 25 nm of FWHM) in four bands with 50 nm of FWHM have been proposed to improve the usability of multispectral image sensors with performing various roles in agriculture as well as detecting FB with other combinations of spectral bands.