A total of 228 domestic and wild animals, including sheep, goats, cows, buffaloes, camels, horses, donkeys, dogs, cats, wild hares, Asiatic jackals, and red foxes were examined for ixodid ticks in the central region of Iraq. Nine species of ixodid ticks belong to two genera namely Hyalomma anatolicum Koch, 1844, H. excavatum Koch, 1844, H. turanicum Pomerantsef, 1946,  H. scupense Delpy, 1946,  H. dromedarii Koch, 1844, H. schulzei Olenev, 1931, Rhipicephalus annulatus (Say, 1821), R. turanicus Pomerantsef & al., 1940 and R. leporis Pomerantsef, 1946 were recovered. Their distribution among hosts and infestation rates were di

In this research, we prepared a hybrid composite material of polymeric matrix hand cast method, composite material has been attended from epoxy resin EP as matrix materials reinforced woven roving fiber jute is constant volume fraction (13%), PVC fibers and woven glass fiber with different fraction on the properties of prepared composite materials to PVC fiber and glass fiber, some of mechanical tests were done at room temperature (impact test and banding test). Result shows that the values of (modulus bending elastic and fracture toughness) increase fraction of fiber with the increase of PVC, E-glass, there include (thermal conductivity and dielectric constant). Also experimental result indicated that the (thermal conductivity and diele

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

The aim of the current study was to develop a nanostructured double-layer for hydrophobic molecules delivery system. The developed double-layer consisted of polyethylene glycol-based polymeric (PEG) followed by gelatin sub coating of the core hydrophobic molecules containing sodium citrate. The polymeric composition ratio of PEG and the amount of the sub coating gelatin were optimized using the two-level fractional method. The nanoparticles were characterized using AFM and FT-IR techniques. The size of these nano capsules was in the range of 39-76 nm depending on drug loading concentration. The drug was effectively loaded into PEG-Gelatin nanoparticles (≈47%). The hydrophobic molecules-release characteristics in terms of controlled-releas

Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem

The huge amount of documents in the internet led to the rapid need of text classification (TC). TC is used to organize these text documents. In this research paper, a new model is based on Extreme Machine learning (EML) is used. The proposed model consists of many phases including: preprocessing, feature extraction, Multiple Linear Regression (MLR) and ELM. The basic idea of the proposed model is built upon the calculation of feature weights by using MLR. These feature weights with the extracted features introduced as an input to the ELM that produced weighted Extreme Learning Machine (WELM). The results showed   a great competence of the proposed WELM compared to the ELM. 

The quality of Global Navigation Satellite Systems (GNSS) networks are considerably influenced by the configuration of the observed baselines. Where, this study aims to find an optimal configuration for GNSS baselines in terms of the number and distribution  of baselines to improve the quality criteria of the GNSS networks. First order design problem (FOD) was applied in this research to optimize GNSS network baselines configuration, and based on sequential adjustment method to solve its objective functions.

FOD for optimum precision (FOD-p) was the proposed model which based on the design criteria of A-optimality and E-optimality. These design criteria were selected as objective functions of precision, whic