Zinc sulfide(ZnS) thin films of different thickness were deposited on corning glass with the substrate kept at room temperature and high vacuum using thermal evaporation technique.the film properties investigated include their absorbance/transmittance/reflectance spectra,band gap,refractive index,extinction coefficient,complex dielectric constant and thickness.The films were found to exhibt high transmittance(59-98%) ,low absorbance and low reflectance in the visible/near infrared region up to 900 nm..However, the absorbance of the films were found to be high in the ultra violet region with peak around 360 nm.The thickness(using optical interference fringes method) of various films thichness(100,200,300,and 400) nm.The band gap meas

In this contribution, density functional theory-based calculations have been carried out to assess the electronic, photocatalytic and optical properties of Ce1-xTixO2 system. Ti incorporation leads to a decrease of Ce 4f states and enhancement of Ti 3d states in the bottom of conduction band. Furthermore, it was found that doping ceria with Ti-like transition metals could evidently shift the absorption of pure CeO2 towards higher wavelength range. These findings can provide some new insights for designing CeO2-based photocatalysts with high photocatalytic performance. To the best of our knowledge, this investigation calculates Mullikan’s charge transfer of Ce1-xTixO2 system for the first time. Charge transfer reveals an ionic bond between

Thin films of CdS:Cu were deposited onto glass substrate temperature 400 °c. The optieal properties have been studied for Cds doped with (1,3, 8) wt% of Cu before and after Gamma irradiation. It was found that the irradiation caused an ( Frenkel defects) where the atom is displaced from its original site leaving vacancy and forming on interstitial atom. It was found the irradiation caused an absorption edge shifting towards long wavelength as a result of the increasing of Cu concentration.

The housing sector in Iraq has suffered from multiple problems, the most prominent of which is the failure of the housing market to achieve housing production that faces population increases and a high number of households.

The research aims to foresight the future of the housing sector,  and to identify the expectations of experts in the development of the housing sector and housing production, in order to overcome the obstacles and problems.

Foresight does not mean forecasting about future events, but rather it is a process and skill aimed at familiarity with providing sufficient knowledge to achieve the desired future goals, Accordingly, adopting a method of future foresight will reduce error,  surprise and s

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

    Identification of complex communities in biological networks is a critical and ongoing challenge since lots of network-related problems correspond to the subgraph isomorphism problem known in the literature as NP-hard. Several optimization algorithms have been dedicated and applied to solve this problem. The main challenge regarding the application of optimization algorithms, specifically to handle large-scale complex networks, is their relatively long execution time. Thus, this paper proposes a parallel extension of the PSO algorithm to detect communities in complex biological networks. The main contribution of this study is summarized in three- fold; Firstly, a modified PSO algorithm with a local search operator is proposed

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).