This manuscript presents several applications for solving special kinds of ordinary and partial differential equations using iteration methods such as Adomian decomposition method (ADM), Variation iterative method (VIM) and Taylor series method. These methods can be applied as well as to solve nonperturbed problems and 3rd order parabolic PDEs with variable coefficient. Moreover, we compare the results using ADM, VIM and Taylor series method. These methods are a commination of the two initial conditions.

The speed of skills has become linked to modern methods of individual and group play, and each of them has begun to serve the other tactically. Through the follow-up of the researchers, they noticed that there is a significant weakness in the speed of performance and slowness in mental preparation, which plays a major role in understanding mental readiness, which is linked to the speed of making decisions during the game, as well as the weakness of the physical speed of the female players, which in turn has an impact on the skill performance of the players of the Iraqi clubs, which are the main supporter of the national team. The study aimed to identify the effect of interactive speed training on the performance of some skills among

An aqueous chemical reaction has been used to prepare antifungal ZnS: Mn nanostructures, from manganese chloride, zinc acetate and thioacetamide in aqueous solution. The nanoparticle size has been controlled using thioglycolic acid as a capping factor. The major feature of the ZnS:Mn nanoparticles of average diameter ~ 2.73 nm is that possible preparing the sample from sources non-toxic precursors. The manufactured ZnS:Mn nanoparticles were identified and characterized to investigate the structure, morphology, composition of components of the nanoparticles and optical properties using (XRD, SEM, EDS and UV-Vis spectroscopy) techniques respectively. The agar dilution mechanism used to evaluate of the antifungal activity using ZnS:Mn nanopart

Specimens of the hedgehog Hemiechinus auritus Gmelin. which were trapped in two places on the Eastern shores of the Tigris River, some 50 and 60 Km, south of Baghdad. central Iraq. were searched for ectoparasites. They revealed the following parasites: One species of Anoplura: polyplex spinulosa (Burm.), family Hoplople uridae, two species of fleas: Synostrnus pallidus (Tasch.) and Ctenocephalides felis (Bouche), family pulicidae, One mite species: Ornithonyssus bacoti (Hirst), family Macronyssidae and two tick species: Rhipicephalus leporis and R. turanicum family Ixodidae. All these ectoparasite species are new records on this hedgehog in Iraq.

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

Cryptography is the process of transforming message to avoid an unauthorized access of data. One of the main problems and an important part in cryptography with secret key algorithms is key. For higher level of secure communication key plays an important role. For increasing the level of security in any communication, both parties must have a copy of the secret key which, unfortunately, is not that easy to achieve. Triple Data Encryption Standard algorithm is weak due to its weak key generation, so that key must be reconfigured to make this algorithm more secure, effective, and strong. Encryption key enhances the Triple Data Encryption Standard algorithm securities. This paper proposed a combination of two efficient encryption algorithms to

A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

The advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse dete