COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduced forecasting procedures into Artificial Neural Network models compared with regression model. Data collected from Al –Kindy Teaching Hospital from the period of 28/5/2019 to 28/7/2019 show an energetic part in forecasting. Forecasting of a disease can be done founded on several parameters such as the age, gender, number of daily infections, number of patient with other disease and number of death . Though, forecasting procedures arise with their private data of tests. This study chats these tests and also offers a set of commendations for the persons who are presently hostile the global COVID-19 disease.
The two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo
... Show MoreThe present study dealt with the removal of methylene blue from wastewater by using peanut hulls (PNH) as adsorbent. Two modes of operation were used in the present work, batch mode and inverse fluidized bed mode. In batch experiment, the effect of peanut hulls doses 2, 4, 8, 12 and 16 g, with constant initial pH =5.6, concentration 20 mg/L and particle size 2-3.35 mm were studied. The results showed that the percent removal of methylene blue increased with the increase of peanut hulls dose. Batch kinetics experiments showed that equilibrium time was about 3 hours, isotherm models (Langmuir and Freundlich) were used to correlate these results. The results showed that the (Freundlich) model gave the best fitting for adsorption capacity. D
... Show MoreThis paper presents a brief study undertaken for improving the performance of information and communication management of construction projects through investing in information and communication technologies (ICT). The work aims at first to investigate and diagnose the problems, challenges, weaknesses, and inefficiencies related to information and communication management in projects in the construction industry of Iraq. Studying the diagnosed matters and the different solutions of ICT to improve project management performance is following the investigation process. The research presents a technological system suggested to process a lot of the diagnosed problems, challenges, weakness, and inefficiencies of the construction projects and t
... Show MoreRG Majeed, AS Ahmed, Jornal of Al-Muthanna for Agricultural Sciences, 2023
In this paper, the bowtie method was utilized by a multidisciplinary team in the Federal Board of Supreme Audit (FBSA)for the purpose of managing corruption risks threatening the Iraqi construction sector. Corruption in Iraq is a widespread phenomenon that threatens to degrade society and halt the wheel of economic development, so it must be reduced through appropriate strategies. A total of eleven corruption risks have been identified by the involved parties in corruption and were analyzed by using probability and impact matrix and their priority has been ranked. Bowtie analysis was conducted on four factors with high score risk in causing corruption in the planning stage. The number and effectiveness of the existing proactive meas
... Show MoreThis paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number
... Show MoreA simple and rapid high performance liquid chromatographic with fluorescence detection method for the determination of the aflatoxin B1, B2, G1 and G2 in peanuts, rice and chilli was developed. The sample was extracted using acetonitrile:water (90:10, v/v%) and then purified by using ISOLUTE multimode solid phase extraction. After the pre-column derivatisation, the analytes were separated within 3.7 min using Chromolith performance RP-18e (100–4.6 mm) monolithic column. To assess the possible effects of endogenous components in the food items, matrix-matched calibration was used for the quantification and validation. The recoveries of aflatoxins that were spiked into food samples were 86.38–104.5% and RSDs were <4.4%. The method was
... Show MoreThe transfer function model the basic concepts in the time series. This model is used in the case of multivariate time series. As for the design of this model, it depends on the available data in the time series and other information in the series so when the representation of the transfer function model depends on the representation of the data In this research, the transfer function has been estimated using the style nonparametric represented in two method local linear regression and cubic smoothing spline method The method of semi-parametric represented use semiparametric single index model, With four proposals, , That the goal of this research is comparing the capabilities of the above mentioned m
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