Quantifying the Euphrates Electric Conductivity Depending on Parameters by Dimensional Analysis Method

The searching about methods to connect the variables with each other to reach equations including multi variables. The dimensional analysis is a method to facilitate the solution of difficult mathematic equations and experimental formulas;therefore methods of simplifying the difficult equations and obtaining a new equation with different variables is needed. In this study will use 2 methods (statically with dimensionally analysis) to obtain electric conductivity of water of Euphrates river by multi parameters that are time (t), temperature (Te), density, viscosity, discharge and water depth in upstream of Alhindya barrage which located in Babylon governorate, Iraq during winter 2019. The equations were obtained for EC with Te and t by data were collected from Alhindya barrage office with R2 = 0.999 and R2 = 0.995 by statically ways. Dimension analysis was utilized via 2 stages. In first stage was obtained on equation of EC with respect to Te, water density (ρ) and dynamic viscosity (μ) with constant time, depth of water and discharge and we obtain on R2 was 0.994 and R2 = 0.986. In second stage was obtained formula of EC with respect to Te, water density (ρ), dynamic viscosity (μ), with variable time, depth of water and discharge with we obtain on R2 = 0.945 and R2 = 0.94. The result of research indicates that applying the dimension analysis to connect more than one variable with each other to find best solutions and best methods to facilitate the solving the equations. From dimension analysis gave a clear visualization of the association of several variables to give a result that helps measure the electrical conductivity of water in the absence of a water test device.

Analysis of normal human retinal vascular network architecture using multifractal geometry

AIM：To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina.METHODS：Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca,Romania,between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images,corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms,applying the standard boxcounting method. Statistical analyses were performed using the Graph Pad In Stat software.RESULTS：The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions（D_q）for q=0,1,2,the width of the multifractal spectrum（Δα=α_（max）-α_（min））and the spectrum arms＇ heights difference（│Δf│）of the normal images were expressed as mean±standard deviation（SD）：for segmented versions,D_0=1.7014±0.0057; D_1=1.6507±0.0058; D_2=1.5772±0.0059; Δα=0.92441±0.0085; │Δf│= 0.1453±0.0051; for skeletonised versions,D_0=1.6303±0.0051; D_1=1.6012±0.0059; D_2=1.5531± 0.0058; Δα=0.65032±0.0162; │Δf│= 0.0238±0.0161. The average of generalized dimensions（D_q）for q=0,1,2,the width of the multifractal spectrum（Δα）and the spectrum arms＇ heights difference（│Δf│）of the segmented versions was slightly greater than the skeletonised versions.CONCLUSION：The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases.

Automated Dynamic Cellular Analysis in Time-Lapse Microscopy

Analysis of cellular behavior is significant for studying cell cycle and detecting anti-cancer drugs. It is a very difficult task for image processing to isolate individual cells in confocal microscopic images of non-stained live cell cultures. Because these images do not have adequate textural variations. Manual cell segmentation requires massive labor and is a time consuming process. This paper describes an automated cell segmentation method for localizing the cells of Chinese hamster ovary cell culture. Several kinds of high-dimensional feature descriptors, K-means clustering method and Chan-Vese model-based level set are used to extract the cellular regions. The region extracted are used to classify phases in cell cycle. The segmentation results were experimentally assessed. As a result, the proposed method proved to be significant for cell isolation. In the evaluation experiments, we constructed a database of Chinese Hamster Ovary Cell’s microscopic images which includes various photographing environments under the guidance of a biologist.

Investigation of Rotor Radial Rotating Error upon AMB System

This paper first suggests the use of the Fourier frequency transmission method of two dimensions function （ 2D FFT） to analyze radial rotating errors that occurred in a rotor. Based on this method a magnetic rotor is measured. The authors point out that the main cause to affect radial rotating accuracy of the rotating shaft at a high speed is the dynamic imbalance of the shaft itself. Finally the feedforward control scheme is suggested to improve the accuracy of the shaft in an active magnetic bearing （ AMB ） system.