Evaporation is one of the major components of the hydrological cycle in the nature, thus its accurate estimation is so important in the planning and management of the irrigation practices and to assess water availability and requirements. The aim of this study is to investigate the ability of fuzzy inference system for estimating monthly pan evaporation form meteorological data. The study has been carried out depending on 261 monthly measurements of each of temperature (T), relative humidity (RH), and wind speed (W) which have been available in Emara meteorological station, southern Iraq. Three different fuzzy models comprising various combinations of monthly climatic variables (temperature, wind speed, and relative humidity) were developed

In this research، a comparison has been made between the robust estimators of (M) for the Cubic Smoothing Splines technique، to avoid the problem of abnormality in data or contamination of error، and the traditional estimation method of Cubic Smoothing Splines technique by using two criteria of differentiation which are (MADE، WASE) for different sample sizes and disparity levels to estimate the chronologically different coefficients functions for the balanced longitudinal data which are characterized by observations obtained through (n) from the independent subjects، each one of them is measured repeatedly by group of  specific time points (m)،since the frequent measurements within the subjects are almost connected an

Abstract

       The grey system model GM(1,1) is the model of the prediction of the time series and the basis of the grey theory. This research presents the methods for estimating parameters of the grey model GM(1,1) is the accumulative method (ACC), the exponential method (EXP), modified exponential method (Mod EXP) and the Particle Swarm Optimization method (PSO). These methods were compared based on the Mean square error (MSE) and the Mean Absolute percentage error (MAPE) as a basis comparator and the simulation method was adopted for the best of the four methods, The best method was obtained and then applied to real data. This data represents the consumption rate of two types of oils a he

The rapid spread of novel coronavirus disease
(COVID19) throughout the world without available
specific treatment or vaccine necessitates alternative
options to contain the disease. Historically, children
and pregnant women were considered high-risk
population of infectious diseases but rarely have been
spotlighted nowadays in the regular COVID-19
updates, may be due to low global rates of incidence,
morbidity, and mortality. However, complications did
occur in these subjects affected by COVID-19. We
aimed to explore the latest updates of
immunotherapeutic perspectives of COVID-19
patients in general population and some added details
regarding pediatric and obstetrical practice.
Immune system boo

The rapid spread of novel coronavirus disease(COVID19) throughout the world without availablespecific treatment or vaccine necessitates alternativeoptions to contain the disease. Historically, childrenand pregnant women were considered high-riskpopulation of infectious diseases but rarely have beenspotlighted nowadays in the regular COVID-19updates, may be due to low global rates of incidence,morbidity, and mortality. However, complications didoccur in these subjects affected by COVID-19. Weaimed to explore the latest updates ofimmunotherapeutic perspectives of COVID-19patients in general population and some added detailsregarding pediatric and obstetrical practice.Immune system boosting strategy is one of therecently emerging issue

Since its start spreed "Severe acute respiratory syndrome coronavirus 2" was discovered in Wuhan, China.that is chargeable COVID-19, a pandemic virus, has end up a widespread fitness hassle everywhere in the global Over 2.1 million people have been affected. We analyze serum concentration of CD4 marker and CD8 marker depend in COVID-19 sufferers, and to make clear a relationship between these variables and disorder Progression and severity For those purpose, (158) sufferers with COVID-19 (showed with the aid of using polymerase chain reaction) and (22) seemingly wholesome human beings have been protected withinside the present day examine and taken into consideration as a manipulate group. All examine population (sufferers and manipulate) h

Background: The global threat of COVID-19 outbreak and on the 11 March 2020, WHO acknowledged that the virus would likely spread to all countries across the globe and declared the coronavirus outbreak a pandemic which is the fifth pandemic since 20 century and this has brought human lives to a sudden and complete lockdown and the confirmed cases of this disease and deaths continue to rise in spite of people around the world are taking important actions to mitigate and decrease transmission and save lives. Objectives: To assess the effect of exercise and physical activity on the immunity against COVID-19. Methods: Collected electronic databases including (Medline, EMBASE, Google Scholar, PubMed and Web of Science) were searched with

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.