• Animal cells and systems
• /
• v.1 no.4
• /
• pp.571-576
• /
• 1997

The playas of the Southern High Plains (SHP) of Texas, USA are an important habitat for over one million wintering waterfowl. However, the recent trend toward the modification of playas for agricultural use is threatening winter habitat of waterfowl in this region. Diurnal activity budgets of wintering mallards (Anas platyrhynchos) were conducted from 1 October to 31 March, 1983-1984, and 1984-1985) at three habitat types; steep-sided pits, terraced pits, and open lakes. All seven activity patterns (feeding, locomotion, resting, comfort, courtship, alert, and agonistic) were different (P<0.05) among the three habitat types for wintering mallards on the SHP of Texas. Terraced pits supported more feeding activity (27.8%) (P<0.001) than steep-sided pits (11.2%) or open lakes (2.6%) due to their abundance of natural seeds and aquatic invertebrates. Hens (17.5%) fed more than drakes (11.7%) (P<0.05). Locomotion (32.2%) and alert (2.8%) behavior across the three habitat types showed the highest level during the early morning (6:00-9:00 AM). Paired mallards rested more (37.9%) than unpaired mallards (25.8%) (P<0.05). Agonistic activity was highest (2.4%) in terraced pits throughout the season.

• Korean Journal of Animal Reproduction
• /
• v.15 no.1
• /
• pp.7-13
• /
• 1991

This study was carried out to investigate the effects of pH of sperm-washing solution, sperm-washing frequency and individual bull on concentration of hydrogen ion in sperm-washed solution and sperm acrosome reaction. The results obtained were as follow. 1. When bovine sperm was washed at 4 times with SHP solution and incubated, the difference of light absorbance between sperm-washing and sperm-washed solution(${\Delta}$Ao-${\Delta}$At) was higher in 2nd sperm-washed solution than that in the other washed solutions. 2. When sperm was thrice washed with SHP solutions of pH 5.99, 6.38, 6.78, 7.10, 7.40, 7.69, 8.15, 8.45, and 8.83, ${\Delta}$Ao-${\Delta}$At was significantly increased at pH7.69 to 8.83, and ${\Delta}$Ao-${\Delta}$At in 1st sperm washed solution was significantly higher than that in 2nd and 3rd sperm washed solution. 3. When sperm of Holstein, KNC and Hereford was thrice washed with SHP solutions of pH 5.99, 6.38, 6.78, 7.10, 7.40, 7.69, 8.15, 8.45, and 8.83, Holstein showed higher ${\Delta}$Ao-${\Delta}$At of sperm Washed solution than KNC and Hereford, and ${\Delta}$Ao-${\Delta}$At in sperm washed solution was significantly increased at 7.69 for Holstein and at 8.15 for KNC and Hereford, respectively. 4. When sperm was thrice with SHP solution of pH 6.8, 7.1 and 7.4, and then incubated in mTALP of pH 7.4 for 15 minutes, in 1st and 2nd sperm washing ${\Delta}$Ao-${\Delta}$At of sperm washed solution was significantly higher at pH 7.1 and 7.4 than at pH 6.8, and the sperm acrosome reaction of pH 6.8, 7.1 and 7.4 was 49.1, 68.8 and 72.9%, respectively. The sperm acrosome reaction of pH 7.1 and 7.4 was higher than that of pH 6.8.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2006.05a
• /
• pp.213-217
• /
• 2006

An intelligent performance diagnostic program using the Neural Network was proposed for PW206C turboshaft engine. It was selected as a power plant for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle) which has been developed by KARI (Korea Aerospace Research Institute). For teaming the NN, a BPN with one hidden, one input and one output layer was used. The input layer had seven neurons of variations of measurement parameters such as SHP, MF, P2, T2, P4, T4 and T5, and the output layer used 6 neurons of degradation ratios of flow capacities and efficiencies for compressor, compressor turbine and power turbine. Database for network teaming and test was constructed using a gas turbine performance simulation program. From application results for diagnostics of the PW206C turboshaft engine using the learned networks, it was confirmed that the proposed diagnostics algorithm could detect well the single fault types such as compressor fouling and compressor turbine erosion.

• Journal of the Korean Society of Propulsion Engineers
• /
• v.10 no.2
• /
• pp.15-22
• /
• 2006

An intelligent performance diagnostic program using the Neural Network was proposed for PW206C turboshaft engine. It was selected as a power plant for the tilt rotor type Smart UAV(Unmanned Aerial Vehicle) which is being developed by KARI (Korea Aerospace Research Institute). For teeming the NN(Neural Network), a BPN(Back Propagation Network) with one hidden, one input and one output layer was used. The input layer has seven neurons: variations of measurement parameters such as SHP, MF, P2, T2, P4, T4 and T5, and the output layer uses 6 neurons: degradation ratios of flow capacities and efficiencies for compressor, compressor turbine and power turbine, respectively, Database for network teaming and test was constructed using a gas turbine performance simulation program. From application of the learned networks to diagnostics of the PW206C turboshaft engine, it was confirmed that the proposed diagnostics algorithm could detect well the single fault types such as compressor fouling and compressor turbine erosion.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.17 no.3
• /
• pp.261-269
• /
• 2015

The purpose of this research is to identify the significance of climate factors related to the significance of change of dry matter yield (DMY) of whole crop maize (WCM) by year through the exploratory data analysis. The data (124 varieties; n=993 in 7 provinces) was prepared after deletion and modification of the insufficient and repetitive data from the results (124 varieties; n=1027 in 7 provinces) of import adaptation experiment done by National Agricultural Cooperation Federation. WCM was classified into early-maturity (25 varieties, n=200), mid-maturity (40 varieties, n=409), late-maturity (27 varieties, n=234) and others (32 varieties, n=150) based on relative maturity and days to silking. For determining climate factors, 6 weather variables were generated using weather data. For detecting DMY and climate factors, SPSS21.0 was used for operating descriptive statistics and Shapiro-Wilk test. Mean DMY by year was classified into upper and lower groups, and a statistically significant difference in DMY was found between two groups (p<0.05). To find the reasons of significant difference between two groups, after statistics analysis of the climate variables, it was found that Seeding-Harvesting Accumulated Growing Degree Days (SHAGDD), Seeding-Harvesting Precipitation (SHP) and Seeding-Harvesting Hour of sunshine (SHH) were significantly different between two groups (p<0.05), whereas Seeding-Harvesting number of Days with Precipitation (SHDP) had no significant effects on DMY (p>0.05). These results indicate that the SHAGDD, SHP and SHH are related to DMY of WCM, but the comparison of R2 among three variables (SHAGDD, SHP and SHH) couldn't be obtained which is needed to be done by regression analysis as well as the prediction model of DMY in the future study.