Search

Digital image processing-computer vision (DIP-CV) systems are used to automate malaria diagnosis through microscopy analysis of thin blood smears. Some variability is observed in the experimental design to evaluate the statistical measures of performance (SMP) of such systems. The objective of this work is assessing good practices when using SMP to evaluate DIP-CV systems for malaria diagnosis. A mathematical model was built to characterize diagnosis using DIP-CV systems and used to obtain curve families showing the relationships among various SMP of these systems, both using theoretical equations and computer simulation. Curve families showing (a) the relationships among the minimum number of positive erythrocytes (RBCs) to be observed, the per object (RBC) sensitivity and the probability to detect at least one positive, (b) per specimen sensitivity vs. total number of RBCs observed for a typical per object sensitivity and a range of parasite densities (c) per object positive predictive value vs. per object specificity for a typical per object sensitivity and various parasite densities. When determining the per specimen sensitivity, the parasite density p showed to have more influence on the number of RBCs that must be analyzed than the per object sensitivity. Measuring p accurately depends heavily upon the per object positive predictive value of the classifier. For low p values, this would require very high per object specificity and a high enough value of observed RBCs to measure this accurately. [ABSTRACT FROM AUTHOR] more...

Heart rate variability (HRV) is used increasingly as a quantitative marker for health in humans and welfare in animals. By evaluating the variability expressed in HRV measures, the information can be used to discern physiological stresses acting on the sympathetic and parasympathetic systems in humans and animals. In equine studies, HRV is used as a noninvasive method to assess stress under various circumstances; however, statistical reliability of HRV measures has not been proven. The purpose of the present study was to establish the statistical stability of HRV measures obtained with a portable heart rate monitor using a test-retest approach. Time and frequency domain measures were obtained for 22 horses during routine activities (free in a box stall, confined on cross ties, and during walking) on two separate days. Within each data set (box stall, n = 19; cross ties, n = 21; walk, n = 7) descriptive statistics were evaluated to determine the group effect between conditions and between days. A comparison of group means on day 1 and day 2 was evaluated using a paired sample t-test. Test-retest reliability estimates were determined with intraclass correlation coefficients (ICCs), which included 95% CI for the ICC estimates. The results indicate that mean values between day 1 and day 2, based on the total group, did not differ across two conditions: box stall and cross ties. When horses were being led at a walk, HRV measurements for mean RR and mean HR were significantly different from day to day; however, no other HRV measurements in either the time or frequency domain were significantly different. ICC estimates of time domain variables were strongest for the box stall condition followed by the cross tie condition and then the walk condition. ICC estimates for the frequency domain variables were strongest for the cross tie condition followed by the walk condition and then the box stall condition. All of the ICCs for frequency domain variables were moderate or strong except for the low frequency:high frequency ratio, which was fair for walking and poor for the stall condition. The results support the hypothesis that HRV measurements from the Polar V800 portable heart rate monitors are statistically reliable and can be easily included in an assessment regimen for horses in different environments. Furthermore, assessment of horses for stress and pain during various circumstances could be reliably conducted using this methodology. [ABSTRACT FROM AUTHOR] more...

Statistical approach to Control Performance Assessment (CPA) is of great practical importance. This is particularly visible in process industry, where there are many PID loops. They are often assessed with measures derived from the Gaussian probabilistic density function. Standard deviation, variance, skewness or kurtosis form the majority of applied indexes. The review of data originating from process industry shows, however, to the contrary, that these signals have rather non-Gaussian properties and are mostly characterized by fat-tailed distribution disable the ability. Investigations show that strong disturbances may significantly disable the capacity of proper assessment. Standard measures often fail in such cases. It is shown that non-Gaussian measures can help with this problem. Various disturbances are tested and compared. Results show that fat-tailed distributions are an interesting alternative. They are less sensitive to disturbance shadowing and still make possible loop dynamic assessment. [ABSTRACT FROM AUTHOR] more...

The quality of a newly merged soil moisture product (ECV_SM v0.1) from active and passive microwave sensors has attracted widespread international attention. The performance evaluation of this product will benefit studies on climate, meteorology, agriculture, hydrology, ecology and the environment. In this study, meteorological station data and the Noah soil moisture product were used to validate the ECV_SM product in China. First, some conventional statistical measures, such as correlation coefficients, bias, root mean square difference (RMSD) and mean relative error (MRE), were computed to describe the level of agreement between the meteorological station data and ECV_SM values. The accuracy was moderately high (the correlation was significant at the 0.05 level), although the two datasets differed slightly for various types of land cover. Compared with cropland and urban and built-up areas, the performance of ECV_SM was best in grassland regions. Second, the triple collocation technique was used to assess the random error in the meteorological station data, Noah soil moisture product and ECV_SM product. The mean errors in these three datasets were 0.108, 0.079 and 0.075 m 3 m −3 , respectively, on July 8, 2010 and 0.099, 0.061 and 0.059 m 3 m −3 , respectively, on October 8, 2010. Only two days of data were used for the triple collocation test as a representative, but this cannot precisely indicate that the test results on any other day correspond with the test results on these two days. Additionally, a trend analysis of ECV_SM during 2003–2010 was carried out using the Mann–Kendall trend test. [ABSTRACT FROM AUTHOR] more...

Copyright of Computer Science (1407-7493) is the property of RTU Publishing House and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) more...