Accurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equilibrium data point with very good accuracy. The developments of this method are applied on 13 binary systems at different temperatures which gives very good accuracy.
This paper aims to propose a hybrid approach of two powerful methods, namely the differential transform and finite difference methods, to obtain the solution of the coupled Whitham-Broer-Kaup-Like equations which arises in shallow-water wave theory. The capability of the method to such problems is verified by taking different parameters and initial conditions. The numerical simulations are depicted in 2D and 3D graphs. It is shown that the used approach returns accurate solutions for this type of problems in comparison with the analytic ones.
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Abstract
The Non - Homogeneous Poisson process is considered as one of the statistical subjects which had an importance in other sciences and a large application in different areas as waiting raws and rectifiable systems method , computer and communication systems and the theory of reliability and many other, also it used in modeling the phenomenon that occurred by unfixed way over time (all events that changed by time).
This research deals with some of the basic concepts that are related to the Non - Homogeneous Poisson process , This research carried out two models of the Non - Homogeneous Poisson process which are the power law model , and Musa –okumto , to estimate th
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The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables. The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
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This study was aimed to evaluate the effect of conventional ingredients replacement with alternative ingredients on growth performance, carcass quality, nutrient digestibility and intestinal microbial of broilers. One hundred twenty Cobb500 broiler chicks were randomly assigned to four diets. Corn, soybean meal and fish meal were replaced with rice waste, meat and bone waste and black soldier fly larvae (BSFL) at 0, 10, 30 and 50% to form four treatments. Body weight gain, feed conversion ratio and digestibility of crude protein and fat were improved in broilers fed the replacement diets. Feed intake was not affected by the treatments suggesting that the replacement diets were well accepted by the chicken. Escherichia coli was decre
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This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1) is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to
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The seasonal behavior of the light curve for selected star SS UMI and EXDRA during outburst cycle is studied. This behavior describes maximum temperature of outburst in dwarf nova. The raw data has been mathematically modeled by fitting Gaussian function based on the full width of the half maximum and the maximum value of the Gaussian. The results of this modeling describe the value of temperature of the dwarf novae star system leading to identify the type of elements that each dwarf nova consisted of.