Publish in OALib Journal
APC: Only $99
Sperm motility analysis has a particular place in male fertility diagnosis. Computerized sperm tracking has an important role in extracting sperm trajectory and measuring sperm’s dynamic features. Due to free movements of sperms in three dimensions, occlusion has remained a challenging problem in this area. This paper aims to present a robust single sperm tracking method being able to handle misdetections in sperm occlusion scenes. In this paper, a robust method of segmentation was utilized to provide the required measurements for a switchable weight particle filtering which was designed for single sperm tracking. In each frame, the target sperm was categorized in one of these three stages: before occlusion, occlusion, and after occlusion where the occlusion had been detected based on sperm’s physical characteristics. Depending on the target sperm stage, particles were weighted differently. In order to evaluate the algorithm, two groups of samples were studied where an expert had selected a single sperm of each sample to track manually and automatically. In the first group, the sperms with no occlusion along their trajectories were tracked to depict the general compatibility of the algorithm with sperm tracking. In the second group, the algorithm was applied on the sperms which had at least one occlusion during their path. The algorithm showed an accuracy of 95% on the first group and 86.66% on the second group which illustrate the robustness of the algorithm against occlusion.
Water is one of the essential
natural resources for the development of life on the earth. In this study we
apply Disjunctive Kriging (DK) and Radial Basis Functions (RBF) for zoning of
groundwater levels. In study area the groundwater levels data have high
skewness. Due to samples unsuitable distribution, data was normalized using
logarithmic and QQPlot methods. Also geostatistical different methods were
evaluated using cross-validation
technique. Results showed that Disjunctive Kriging (DK) compared to
Radial Basis Function (RBF) has the higher accuracy and the best model of
Semivariogramis Exponential model. Also the groundwater levels decreases
from north to south of the Shahrekord plain, Iran. Finally, Disjunctive Kriging
was selected as the most appropriate method of investigation for the groundwater
levels zoning Sahrekord plain.
Exact prediction of
evapotranspiration is necessary for study, design and management of irrigation
systems. In this research, the suitability of soft computing approaches namely,
fuzzy rule base, fuzzy regression and artificial neural networks for estimation
of daily evapotranspiration has been examined and the results are compared to
real data measured by lysimeter on the basis of reference crop (grass). Using
daily climatic data from Haji Abad station in Hormozgan, west of Iran,
including maximum and minimum temperatures, maximum and minimum relative
humidities, wind speed and sunny hours, evapotranspiration was predicted by
soft computing methods. The predicted evapotranspiration values from fuzzy rule
base, fuzzy linear regression and artificial neural networks show root mean
square error (RMSE) of 0.75, 0.79 and 0.81 mm/day and coefficient of
determination of (R2) of 0.90, 0.87 and 0.85, respectively.
Therefore, fuzzy rule base approach was found to be the most appropriate method
employed for estimating evapotranspiration.
In recent decades population
increasing and development of agriculture and also being mountainous and climatic
characteristics of Sefieddasht plain and also nonuniform distribution of rainfall
in study area have led to irregular use of groundwater resources in study area.
This issue has led to critical condition of groundwater resources in Sefieddasht
plain. This research was carried out to determine the suitable areas for
artificial recharge in Sefieddasht plain. Four factors namely, alluvial
quality, alluvial thickness, slope, and infiltration rate parameters were
explored and maps produced and classified using GIS. Fuzzy logic model was used
to determine the suitable areas for artificial recharge. Finally land use maps were used as a filter. Based on results 4.12% of region was recognized as
suitable area for artificial recharge.