
In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl
... Show MoreThis work explores the advancement and potential of solar‐powered humidification–dehumidification (HDH) desalination systems, addressing the critical challenge of global water scarcity. Emphasizing solar‐powered humidifiers in HDH systems presents an innovative solution per the urgent demand for sustainable freshwater sources utilizing abundant energy resources. This work reviews various humidifier designs, pointing out their crucial role in the efficiency and yield of HDH desalination units and their operational, maintenance, and scaling issues. Key factors, such as design effectiveness, water‐vapor capacity, and material selection, are assessed to understand their impact on the system's ove
The presented work shows a preliminary analytic method for estimation of load and pressure distributions on low speed wings with flow separation and wake rollup phenomena’s. A higher order vortex panel method is coupled with the numerical lifting line theory by means of iterative procedure including models of separation and wake rollup. The computer programs are written in FORTRAN which are stable and efficient.
The capability of the present method is investigated through a number of test cases with different types of wing sections (NACA 0012 and GA(W)-1) for different aspect ratios and angles of attack, the results include the lift and drag curves, lift and pressure distributions along the wing s
... Show MoreHeart failure (HF) is characterized by family history and clinical examination combined with diagnostic tools such as electrocardiogram, chest x-ray and an assessment of left ventricular function by echocardiography. An early diagnosis of heart failure is still based on symptoms of dyspnea, fatigue and signs of fluid overload. Serum N-terminal pro-B-type natriuretic peptide (NT-pro BNP) is cardiac biomarker has emerged as potential predictor of heart failure. It is used as a sensitive biomarker in diagnosis and assessment severity of heart failure. This study assed the diagnostic value of (NT-pro BNP), in Iraqi children patients with heart failure and its correlation with LVEF% especially in emergency rooms of hospitals.Ninety (90) consecut
... Show MoreHydraulic fracturing is considered to be a vital cornerstone in decision making of unconventional reservoirs. With an increasing level of development of unconventional reservoirs, many questions have arisen regarding enhancing production performance of tight carbonate reservoirs, especially the evaluation of the potential for adapting multistage hydraulic fracturing technology in tight carbonate reservoirs to attain an economic revenue.
In this paper we present a feasibility study of multistage fractured horizontal well in typical tight carbonate reservoirs covering different values of permeability. We show that NPV is the suitable objective function for deciding on the optimum number
In this research, we present a nonparametric approach for the estimation of a copula density using different kernel density methods. Different functions were used: Gaussian, Gumbel, Clayton, and Frank copula, and through various simulation experiments we generated the standard bivariate normal distribution at samples sizes (50, 100, 250 and 500), in both high and low dependency. Different kernel methods were used to estimate the probability density function of the copula with marginal of this bivariate distribution: Mirror – Reflection (MR), Beta Kernel (BK) and transformation kernel (KD) method, then a comparison was carried out between the three methods with all the experiments using the integrated mean squared error. Furthermore, some
... Show MoreDiscourse markers are expressions used to connect sentences to what comes before or after and indicate a speaker's attitude to what he is saying.As linguistic items, they have important functions in discourses of various styles or registers. And being connective elements, discourse markers relate sentences, clauses and paragraphs to each other. "One of the most prominent function of discourse markers, however, is to signal the kinds of relations a speaker perceives between different parts of the discourse". (Lenk 1997: 2) Through political discourse, different types of discourse markers are used. This paper deals with the importance and functions of discourse markers and tries to shed light on the kinds of discourse markers used in polit
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