A Short-Term Solar Photovoltaic Power Optimized Prediction Interval Model Based on FOS-ELM Algorithm

Solar energy conversion efficiency has improved by the advancement technology of photovoltaic (PV) and the involvement of administrations worldwide. However, environmental conditions influence PV power output, resulting in randomness and intermittency. These characteristics may be harmful to the power scheme. As a conclusion, precise and timely power forecast information is essential for the power networks to engage solar energy. To lessen the negative impact of PV electricity usage, the offered short-term solar photovoltaic (PV) power estimate design is based on an online sequential extreme learning machine with a forgetting mechanism (FOS-ELM) under this study. This approach can replace existing knowledge with new information on a continuous basis. The variance of model uncertainty is computed in the first stage by using a learning algorithm to provide predictable PV power estimations. Stage two entails creating a one-of-a-kind PI based on cost function to enhance the ELM limitations and quantify noise uncertainty in respect of variance. As per findings, this approach does have the benefits of short training duration and better reliability. This technique can assist the energy dispatching unit list producing strategies while also providing temporal and spatial compensation and integrated power regulation, which are crucial for the stability and security of energy systems and also their continuous optimization.

Reliability and Validity of the SHFT Running Power Meter

The SHFT device is a novel running wearable consisting of two pods connected to your smartphone issuing several running metrics based on accelerometer and gyroscope technology. The purpose of this study was to investigate the reliability and validity of the power output (PO) metric produced by the SHFT device. To assess reliability, 12 men ran on an outdoor track at 10.5 km·h−1 and 12 km·h−1 on two consecutive days. To assess validity, oxygen uptake (VO2) and SHFT data from eight men and seven women were collected during incremental submaximal running tests on an indoor treadmill on one to four separate days (34 tests in total). SHFT reliability on the outdoor track was strong with coefficients of variance (CV) of 1.8% and 2.4% for 10.5 and 12 km·h−1, respectively. We observed a very strong linear relationship between PO and VO2 (r2 = 0.54) within subjects, and a very strong linear relationship within each subject within each treadmill test (r2 = 0.80). We conclude that SHFT provides a reliable running power estimate and that a very strong relationship between SHFT-Power and metabolic rate exists, which places SHFT as one of the leading commercially available running power meters.

The utility of a closed breeding colony of Peromyscus leucopus for dissecting complex traits

Although Peromyscus leucopus (deermouse) is not considered a genetic model system, its genus is well suited for addressing several questions of biologist interest, including the genetic bases of longevity, behavior, physiology, adaptation, and its ability to serve as a disease vector. Here we explore a diversity outbred approach for dissecting complex traits in Peromyscus leucopus, a non-traditional genetic model system. We take advantage of a closed colony of deer-mice founded from 38 individuals between 1982 and 1985 and subsequently maintained for 35+ years (~40-60 generations). From 405 low-pass (~1X) short-read sequenced deermice we accurately imputed genotypes at 17,751,882 SNPs. Conditional on observed genotypes for a subset of 297 individuals, simulations were conducted in which a QTL contributes 5% to a complex trait under three different genetic models. The power of either a haplotype- or marker-based statistical test was estimated to be 15-25% to detect the hidden QTL. Although modest, this power estimate is consistent with that of DO/HS mice and rat experiments for an experiment with ~300 individuals. This limitation in QTL detection is mostly associated with the stringent significance threshold required to hold the genome-wide false positive rate low, as in all cases we observe considerable linkage signal at the location of simulated QTL, suggesting a larger panel would exhibit greater power. For the subset of cases where a QTL was detected, localization ability appeared very desirable at ~1-2Mb. We finally carried out a GWAS on a demonstration trait, bleeding time. No tests exceeded the threshold for genome-wide significance, but one of four suggestive regions co-localizes with Von Willebrand factor. Our work suggests that complex traits can be dissected in founders-unknown P. leucopus colony mice in much the same manner as founders-known DO/HS mice and rats, with genotypes obtained from low pass sequencing data. Our results further suggest that the DO/HS approach can be powerfully extended to any system in which a founders-unknown closed colony has been maintained for several dozen generations.

Non-Inferiority Test for a Continuous Variable with a Flexible Margin in an Active Controlled Trial : An Application to the "Stratall ANRS 12110 / ESTHER" Trial

Background : The non-inferiority trials are becoming increasingly popular in public health and clinical research. The choice of the non-inferiority margin is the cornerstone of the non-inferiority trial. When the effect of active control intervention is unknown, it can be interesting to choose the non-inferiority margin as a function of the active control intervention effect. In this case, the uncertainty surrounding the non-inferiority margin should be accounted for in statistical tests. In this work, we explored how to perform the non-inferiority test with a flexible margin for continuous endpoint.Methods: It was proposed in this study two procedures for the non-inferiority test with a flexible margin for the continuous endpoint. The proposed test procedures are based on test statistic and confidence interval approach. Simulations have been used to assess the performances and properties of the proposed test procedures. An application was done on clinical real data, which the purpose was to assess the efficacy of clinical monitoring alone versus laboratory and clinical monitoring in HIV-infected adult patients.Results : Basically, the two proposed test procedures have good properties. In the test based on a statistic, the actual type 1 error rate estimate is approximatively equal to the nominal value. It has been found that the confidence interval level determines approximately the level of significance. The $80\%$ , $90\%$ , and $95\%$ one-sided confidence interval levels led approximately to a type I error of $10\%$ , $5\%$ and $2.5\%$ respectively. The power estimate was almost $100\%$ for two proposed tests, except for the small scale values of the reference treatment where the power was relatively low when the sample sizes were small.Conclusions : Based on type I error rate and power estimates, the proposed non-inferiority hypothesis test procedures have good performance and are applicable in practice.Trial registration : The trial data used in this study was from the "Stratall ANRS 12110 / ESTHER", registered with ClinicalTrials.gov, number NCT00301561. Date : March 13, 2006, url : https://clinicaltrials.gov/ct2/show/NCT00301561.

Numerical Investigation of an Experimental Ocean Current Turbine Based on Blade Element Momentum Theory (BEM)

Ocean currents are one of the alternative sources of green, sustainable, and renewable energy that could generate low-cost electric power without any pollution due to the burning of fossil fuels. Due to the density of the water, ocean currents can produce a significant amount of energy even with a very small current velocity field. In this study, a comprehensive performance analysis of 3-blade horizontal-axis Ocean Current Turbine (OCT) is shown to achieve optimal rpm (revolutions per minute) to match environmental conditions in order to harvest the maximum possible energy from OCT in ocean currents. Our approach is to use Blade Element Momentum (BEM) theory in order to estimate hydrodynamic loads for the turbine; specifically, the design of the OCT blades is based on a FX77-W121 type airfoil. We use JavaFoil to analyze and determine hydrodynamic lift and drag coefficients with respect different angles of attack for the hydrofoil profiles in seawater. After validation of blade design characteristics and obtaining the local coefficients of each hydrofoil cross-sections, we transfer them to our in-house-developed Blade Element Momentum Theory (BEM) code in order to achieve the estimation of performance analysis of the OCT in order to get maximum power and ideal torque and thrust. This performance analysis with BEM model of the OCT is an important step for further analysis due to having different incoming flow speeds in actual time-varying sea conditions. Indeed, the OCT will encounter different incoming ocean current speeds during operation. Therefore, this approach is used to get an accurate brake power estimate of the OCT in different operational current speeds. In addition, this performance analysis of the OCT is going to be utilized in designing and developing a test model for the physical towing tank experiment for later investigation.

Non-inferiority test for a continuous variable with a flexible margin in an active controlled trial : An application to the "Stratall ANRS 12110 / ESTHER" trial

Background: The non-inferiority trials are becoming increasingly popular in public health and clinical research. The choice of the non-inferiority margin is the cornerstone of the non-inferiority trial. When the effect of active control intervention is unknown, it can be interesting to choose the non-inferiority margin as a function of the active control intervention effect. In this case, the uncertainty surrounding the non-inferiority margin should be accounted for in statistical tests. In this work, we explored how to perform the non-inferiority test with a flexible margin for continuous endpoint.Methods: It was proposed in this study two procedures for the non-inferiority test with a flexible margin for the continuous endpoint. The proposed test procedures are based on test statistic and confidence interval approach. Simulations have been used to assess the performances and properties of the proposed test procedures. An application was done on clinical real data, which the purpose was to assess the efficacy of clinical monitoring alone versus laboratory and clinical monitoring in HIV-infected adult patients.Results: Basically, the two proposed test procedures have good properties. In the test based on a statistic, the actual type 1 error rate estimate is approximatively equal to the nominal value. It has been found that the confidence interval level determines approximately the level of significance. The 80%, 90%, and 95%one-sided confidence interval levels led approximately to a type I error of 10%, 5% and 2.5% respectively. The power estimate was almost 100% for two proposed tests, except for the small scale values of the reference treatment where the power was relatively low when the sample sizes were small.Conclusions: Based on type I error rate and power estimates, the proposed non-inferiority hypothesis test procedures have good performance and are applicable in practice.Trial registration: The trial data used in this study was from the ”Stratall ANRS 12110 / ESTHER”, registered with ClinicalTrials.gov, number NCT00301561. Date : March 13, 2006, url : https://clinicaltrials.gov/ct2/show/NCT00301561.

On the local properties of solutions of the nonlinear Beltrami equation

A power estimate of the area of the image of a disk for regular homeomorphisms possessing the Luzin N-property is obtained in terms of the p-angular dilation for p>2. The result generalizes the known estimate by M.A. Lavrent'ev. A number of theorems on the asymptotic behavior of regular homeomorphic solutions of the nonlinear Beltrami equation are proved, and an extreme analog of the Ikoma-Schwartz lemma is formulated.

CFD analysis of flashing flow in two-phase geothermal turbine design

A thermal power plant for the East African Rift countries is under study for combined energy and freshwater generation using geothermal water, available at above 500 kPa pressure and temperature exceeding 150°C. This article presents the computational fluid dynamics (CFD) model and analysis of the two-phase turbine used for power generation in this total flow thermal plant. Flash boiling was implemented using a two-fluid multiphase model with the thermal phase-change criteria for heat, mass, and momentum transfer in the CFD solver ANSYS CFX. Initially, flashing flow in a converging–diverging nozzle was validated. This stationary nozzle model was then extended to a curved rotating nozzle reaction turbine and the results of flow and power were evaluated against available test data at 400 kPa feed water pressure under subcooled condition of 117°C and a very low backpressure of 6 kPa. Flow through this turbine was predicted within 8% deviation. An overestimate in thermodynamic power by 30–50% was predicted at speeds below 4000 rpm, while at the design speed of 4623 rpm the deviation was less than 5%. Rotor torque and hence power estimate was found to be dependent on the bubble size, bubble number density, and heat transfer parameters prescribed in the CFD model. The vapour dryness fraction at turbine exit was close to an isentropic expansion vapour quality. The isentropic efficiency was 7.5–17% for the analysed speed range.

Power Analysis by Simulation using R and simglm

Power is a task that is commonly done prior to collecting data for a primary study. In most cases closed-form solutions are used to estimate power which may statistical assumptions to be able to perform the computations, for example assume residuals are normally distributed. In real-world data, these statistical assumptions may not hold, therefore estimates of power when these assumptions are assumed will likely be inflated. Power by simulation is another way to compute power estimates and offers significant flexibility to the user to explore the impact of various statistical assumption violations may have on power. This tutorial uses the simglm R package to perform the power by simulation. The simglm package provides a framework to simulate data from generalized linear mixed models which includes a wide variety of models. In addition, functions to perform replications and to compute power estimate summaries are available for users to take advantage of. Two worked examples are shown, one for a two-sample t-test and another within a repeated measures or longitudinal framework.