MO Khudhair, 2020

Abstract

The use of modern scientific methods and techniques, is considered important topics to solve many of the problems which face some sector, including industrial, service and health. The researcher always intends to use modern methods characterized by accuracy, clarity and speed to reach the optimal solution and be easy at the same time in terms of understanding and application.

the research presented this comparison between the two methods of solution for linear fractional programming models which are linear transformation for Charnas & Cooper , and denominator function restriction method through applied on the oil heaters and gas cookers plant , where the show after reac

Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio

Smart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things,

Islamic law has relied on a number of sources in order to denote the rulings issued by them, including what is original and what is sub, and it is known to all scholars, that the Prophet's Sunnah is the second major source after the Koran, which separated the overall and devoted its year and restricted absolute. God Almighty obeyed the owner and his followers, and that his obedience of obedience to God Almighty said: (Who obeys the messenger has obeyed God) (women: 80), and then between the peasant who believes in him and his victory and follow him, he said: (and he said: And the one who was revealed with them were the successful ones (al-A'raf: 157).
     It is known that the Sunnah commanded to follow is the

4 Blood Res 2018;53:314-319. Received on August 11, 2018 Revised on August 30, 2018 Accepted on August 30, 2018 Background Iron overload is a risk factor affecting all patients with thalassemia intermedia (TI). We aimed to determine whether there is a relationship of serum ferritin (SF) and alanine ami- notransferase (ALT) with liver iron concentration (LIC) determined by R2 magnetic reso- nance imaging (R2-MRI), to estimate the most relevant degree of iron overload and best time to chelate in patients with TI. Methods In this cross-sectional study, 119 patients with TI (mean age years) were randomly se- lected and compared with 120 patients who had a diagnosis of thalassemia major (TM). Correlations of LIC, as determined by R2-MRI, with SF

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.