A Broadband Meta surface Based MIMO Antenna with High Gain and Isolation For 5G Millimeter Wave Applications

This paper proposes a Broadband Meta surface-based MIMO Antenna with High Gain and Isolation For 5G Millimeter applications. A single antenna is transformed into an array configuration to improve gain. As a result, each MIMO antenna is made up of a 1x2 element array supplied by a concurrent feedline. A 9x6 Split Ring Resonator (SRR) elongated cell is stacked above the antenna to improve gain and eliminate the coupling effects between the MIMO components. The substrate Rogers 5880 with a thickness of 0.787mm and 1.6mm is used for the antenna and meta surface. Furthermore, antenna performance is assessed using S-parameters, MIMO characteristics, and radiation patterns. The final designed antenna supports 5G applications by embracing the mm-wave frequency spectrum at Ka-band, there is a noticeable increase in gain. In addition, once the meta surface is introduced, there is an improvement in isolation.&nbsp

Shannon and Fuzzy entropy based evolutionary image thresholding for image segmentation

Image segmentation is a very important and pre-processing step in image analysis. The conventional multilevel thresholding methods are efficient for bi-level thresholding because of its simplicity, robustness, less convergence time and accuracy. However, a mass of computational cost is needed and efficiency is broken down as an exhaustive search is utilized for finding the optimal thresholds, which results in application of evolutionary algorithm and swarm intelligence to obtain the optimal thresholds. The main aim of image segmentation was to segregate the foreground from background. For the first time this paper established a naturally inspired firefly algorithm based multilevel image thresholding for image segmentation by maximizing Shannon entropy or Fuzzy entropy. The proposed algorithm is tested on standard set of images and results are compared with the Shannon entropy or Fuzzy entropy based methods that are optimized by Differential Evolution (DE), Particle Swarm Optimization (PSO) and bat algorithm (BA). It is demonstrated that the proposed method shows better performance in objective function, structural similarity index, peak signal to noise ratio, misclassification error and CPU time than state of art methods. Keywords: Image segmentation, Image thresholding, Fuzzy entropy, Shannon entropy, Particle Swarm Optimization, Firefly algorith

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran