A solar irradiance estimation technique via curve fitting based on dual-mode Jaya optimization

Solar irradiance is a crucial environmental parameter for optimal control of photovoltaic (PV) systems. However, precise measurements of the solar irradiance are difficult since the irradiation sensors (i.e., pyranometer or pyrheliometer) are expensive and hard to calibrate. This paper proposes a cost-effective and accurate method for estimating the solar irradiance with a PV module via curve fitting. A dual-mode Jaya (DM-Jaya) optimization algorithm is introduced to extract the real-time value of solar irradiance from the measured PV characteristics data by using two search strategies. The step sizes of a random walk are taken from even and Lévy distribution distributions in different searching phases. Compared with the traditional irradiance sensors, the proposed estimator does not require additional circuit and obtains relatively lower error rates. A comparative study of seven population-based optimization algorithms for the optimal design of the estimator is presented. These algorithms include particle swarm optimization (PSO), cuckoo search (CS), Jaya, simulated annealing (SA), genetic algorithm (GA), supply-demand-based optimization (SDO), and the proposed DM-Jaya algorithm. Simulations and experimental results reveal that DM-Jaya outperforms the other optimization algorithms in terms of the estimation speed and accuracy

Growth of young HIV-infected and HIV-exposed children in western Kenya: A retrospective chart review

Introduction The objective of this study was to determine the growth patterns, rates of malnutrition, and factors associated with malnutrition in children born to HIV-infected mothers in western Kenya using data from an electronic medical record system. Methods This study was a retrospective chart review of HIV-infected (HIV+) and–exposed (HEU) children (<5 years) using data collected prospectively in the course of routine clinical care and stored in the electronic medical record system in western Kenya between January 2011 and August 2016. Demographics and anthropometrics were described, with Chi-square testing to compare proportions. Multiple variable logistic regression analysis was used to identify correlates of children being stunted, underweight, and wasted. We also examined growth curves, using a resampling method to compare the areas under the fitted growth curves to compare males/females and HIV+/HEU. Results Data from 15,428 children were analyzed. The children were 51.6% (n = 7,955) female, 5.2% (n = 809) orphans, 83.3% (n = 12,851) were HEU, and 16.7% (n = 2,577) were HIV+. For HIV+ children assessed at 24 months, 50.9% (n = 217) were stunted, 26.5% (n = 145) were underweight, and 13.6% (n = 58) were wasted, while 45.0% (n = 577) of HEU children were stunted, 14.8% (n = 255) were underweight, and 5.1% (n = 65) were wasted. When comparing mean z-scores, HIV+ children tended to have larger and earlier dips in z-scores compared to HIV-exposed children, with significant differences found between the two groups (p<0.001). Factors associated with an increased risk of malnutrition included being male, HIV+, and attending an urban clinic. Maternal antiretroviral treatment during pregnancy and mixed feeding at 3 months of age decreased the risk of malnutrition. Conclusions HIV+ and HEU children differ in their anthropometrics, with HIV+ children having overall lower z-scores. Continued efforts to develop and implement sustainable and effective interventions for malnutrition are needed for children born to HIV+ mothers