Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models were applied in the health sector to predict the numbers of people infected with the Covid-19 virus in Iraq where the data were collected via the website of the Iraqi Ministry of Health through the daily epidemiological situation of all Iraqi provinces for the period (2021\3\28 to 2021\8\15). When analyzing, studying, and comparing these models, the researcher noted that the hybrid model outperformed other models because it had the lowest value for the MSE, RMSE, MAE, and MAPE so it was used to predict future values.
This paper proposes a novel finite-time generalized proportional integral observer (FTGPIO) based a sliding mode control (SMC) scheme for the tracking control problem of high order uncertain systems subject to fast time-varying disturbances. For this purpose, the construction of the controller consists of two consecutive steps. First, the novel FTGPIO is designed to observe unmeasurable plant dynamics states and disturbance with its higher time derivatives in finite time rather than infinite time as in the standard GPIO. In the FTGPO estimator, the finite time convergence rate of estimations is well achieved, whereas the convergence rate of estimations by classical GPIO is asymptotic and slow. Secondly, on the basis of the finite and fast e
... Show More This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case s
Objective Tea lovers are increasing worldwide. We hope that this report is the first to discuss the possible impacts of high black tea consumption on gestational weight gain (GWG) and birth parameters. Methods Throughout one year, a total of 7,063 pregnant ladies coming for first antenatal visit were screened in a major tertiary center. Of them, 1,138 were involved and divided according to their preference into 3 groups: excessive tea (ET), usual tea (UT), and mixed beverages group. The study included women who gave birth to healthy neonates. Results The rate of ET consumption was 4.13% with a total of 41 cases. The UT group (controls) comprised 94 women. ET was significantly associated (P<0.05) with maternal age, parity, occupation, smokin
... Show MoreIn this study, the response of ten composite post-tensioned concrete beams topped by a reinforced concrete deck with adequate reinforcing shear connectors is investigated. Depending on the concrete compressive strength of the deck slab (20, 30, and 40 MPa), beams are grouped into three categories. Seven of these beams are exposed to a fire attack of 700 and 800 °C temperature simultaneously with or without the presence of a uniformly distributed sustained static loading. After cooling back to ambient temperature, these composite beams are loaded up to failure, using a force control module, by monotonic static loading in a four-point-bending setup with two symmetrical concentrated loads applied in
In this paper, fire resistance and residual capacity tests were carried out on encased pultruded glass fiber-reinforced polymer (GFRP) I-beams with high-strength concrete beams. The specimens were loaded concurrently under 25% of the ultimate load and fire exposure (an increase in temperature of 700 °C) for 70 min. Subsequently, the fire-damaged specimens were allowed to cool and then were loaded statically until failure to explore the residual behaviors. The effects of using shear connectors and web stiffeners on the residual behavior were investigated. Finite Element (FE) analysis was developed to simulate the encased pultruded GFRP I-beams under the effect of fire loading. The thermal analyses were performed using the general-pu
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