Multiple checks on the datapoint strong dataset

Multiple checks on the 108 datapoint strong dataset revealed that certain values of length and breadth in the dataset created with Heparin (dosage – 260I.U. in 250ml of porcine blood) had values incorporated from a different scale of measurement. Given that a set of values came from a different measurement scale, these values contributed to the non-normal distribution of the length and breadth parameters. Fig. 4 presents the length, breadth distribution with the actual values by replacing the erroneous ones. The length and breadth values for 9 datapoints created with a 2.5cc subcutaneous syringe with needle containing blood (250ml blood thoroughly admixed with 260I.U. of Heparin), were found to follow normal distribution with Shapiro Wilk value of 0.846 (p=0.068>0.05) and .889 (p=0.194>0.05) respectively. The features length, breadth and logarithm of the total number of spines for stains, formed by letting blood thoroughly admixed with 2mg of Warfarin to drip from a 2.5cc subcutaneous syringe without needle filled to capacity, were found to follow normal distribution with Shapiro Wilk values of 0.897 (p=0.236>0.05), 0.886 (p=0.180>0.05) and .838 (p=.055>0.05) respectively. The points that include 95% of the length observations are 1.422 (mean)±1.96×0.35978 (standard deviation), giving a range of 0.7170312 and 2.1273688 [based on Empirical Rule]. There stands only 5% chance that the cp-690550 mean will lie outside the points defined by 1.422±2.306×11,993 (standard error) [tα/2,df= 2.306 (df=8)], giving a range of 1.14544 and 1.69856. The points that include 95% of the breadth observations for the stains are 1.0111 (mean)±1.96×0.16915 (standard deviation), giving a range of 0.679566 and 1.342643. There stands only 5% chance that the population mean will lie outside the points defined by 1.0111±2.30×0.05638 (standard error) [tα/2,df= 2.306 (df=8)], giving a range of 0.88109 and 1.141112. The points that include 95% of the logarithm of the total number of spines for the stains formed for the nine stains under consideration are 2.04±1.96×1.34371, giving a range of and 4.674, given that the number of spines cannot be negative. Again, there is 95% chance that the mean of the total number of spines for the entire population will lie in the range 2.04±2.30×44,790, defined by the points 1.0058 and 3.0716 (refer Fig. 5). When the angle of impact and fall height is taken into consideration in accordance with the source of emission and dosage when grouping stain patterns, the standard deviation from the mean and the median absolute deviation were found to be much lower than the standard deviation value for the length, breadth and total number of spines for stains grouped only on the basis of source of emission and dosage. For Sheet 2 in the dataset, the mean and standard deviation of length, breadth and total number of spines for 9 stains grouped on the basis of dosage (2mg of Warfarin in 250ml of blood), emission point (2.5cc subcutaneous syringe without needle), fall height (40cm) and angle of impact (60°) are represented in Table 7. The standard deviation of the calculated angle of impact from the intended angle of impact irrespective of other specification was calculated for the 108 datapoint strong dataset. The variance and standard deviation of the calculated angle of impact from the median value of 30° across 36 datapoints was calculated as 4.8322 degree2 and 2.1982° respectively. The standard deviation of the calculated angle of impact from the intended angle of impact (60°) and median value of 59° was recorded as 5.6470° and 5.1695° respectively. For 90° angle of impact the standard deviation and variance was recorded as 0°.
Usage hints Image pre-processing is an integral step towards removing noise, artefacts (such as ruler, pencil markings in this case etc.) from an image. Extraction of the Region of Interest (ROI) from an image is the first step towards selection or extraction of relevant features from the image. In order to aid users, the authors have developed an algorithm for pre-processing and thereby extraction of Region of Interest from the images documented in Sheet 1 and 2. Fig. 6 represents a block diagram of the algorithm that might be used for pre-processing and ROI extraction from the image. The time complexity of the algorithm presented is O(n2).