Determination of the width of sodium ring around iris Relationship between cholesterol values and sodium ring width Proposal of an empirical method with linear/multilinear regression analysis The sodium ring, which is one of the symptoms of high cholesterol, is a colored ring close to the whiteness formed around the iris. The examination of this ring and its follow up can be considered as an alternative to control the level of cholesterol. Figure A. Iris analysis to determine sodium ring width Purpose: The purpose of this study is to calculate of the sodium ring width and then to determine the relationship between the sodium ring width and the level of cholesterol. Theory and Methods: Sodium ring widths were determined using eye images obtained from 15 different patients. The relationship between these values and the cholesterol values of the patients was investigated. Results: Novel methods for determining sodium ring width have been proposed using, total cholesterol, LDL, HDL, and triglycerides. Conclusion: With the use of the proposed method, the sodium ring width on iris can be determined with 86% accuracy by using cholesterol values.
There is a significant increase in the use of wireless communication and it is expected that this increase will continue progressively. In the near future, cellular network technologies are expected to be capable of increasing the area throughput hundreds of times in order to cope with the increase in data traffic. Increasing spectral efficiency (SE) with massive multi-input multi-output (Massive MIMO) systems is one of the main methods used to meet these expectations. SE means the amount of information transmitted successfully with each complex sample. Increasing the transmission power and the number of active antennas while increasing the SE increases the amount of energy consumed to very high levels. The fact that high energy consumption is harmful to the environment and costly makes it important to increase energy efficiency (EE). Various studies are carried out with the aim of bringing optimum levels of the SE and EE parameters which has trade-off between each other. Multi-objective intelligent optimization techniques are applied on the trade-off for detecting optimum SE-EE values. In this paper, multi-objective genetic algorithm (MOGA) and multi-objective differential evolution algorithm (MODEA) are used to obtain optimum values of certain factors (amount of transmit power, number of active antennas and number of user equipments). At the last stage, the calculations made for all values of the mentioned factors and the optimization results (performed in a relatively short time compared to these calculations) are shown on the same graph.
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