This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case s

Hydrate dissociation equilibrium conditions for carbon dioxide + methane with water, nitrogen + methane with water and carbon dioxide + nitrogen with water were measured using cryogenic sapphire cell. Measurements were performed in the temperature range of 275.75 K–293.95 K and for pressures ranging from 5 MPa to 25 MPa. The resulting data indicate that as the carbon dioxide concentration is increased in the gas mixture, the gas hydrate equilibrium temperature increases. In contrast, by increasing the nitrogen concentration in the gas mixtures containing methane or carbon dioxide decreased the gas hydrate equilibrium temperatures. Furthermore, the cage occupancies for the carbon dioxide + methane system were evaluated using the Van der Wa

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

This work deals with preparation of zeolite 5A from Dewekhala kaolin clay in Al-Anbar region for drying and desulphurization of liquefied petroleum gas. The preparation of zeolite 5A includes treating kaolin clay with dilute hydrochloric acid 1N, treating metakaolin with NaOH solution to prepare 4A zeolite, ion exchange, and formation. For preparation of zeolite 4A, metakaolin treated at different temperatures (40, 60, 80, 90, and 100 °C) with different concentrations of sodium hydroxide solution (1, 2, 3, and 4 N) for 2 hours. The zeolite samples give the best relative crystallinity of zeolite prepared at 80 °C with NaOH concentration 3N (199%), and at 90 and 100°C with NaOH concentration solution 2N (184% and 189%, respectively). Ze

   This article includes the preparation of luminescence materials from rare earth (Eu ) ion doping Yttrium Oxide (Y₂O₃) 70% and SiO₂ 25% and study the characteristics of phosphors for ultraviolet to visible conversion. The phosphor materials have been synthesized by two steps: Preparing the powder by solid state method using Y₂O₃, SiO₂ and Eu₂O₃ with doping materials concentration (70%, 25% and 5%) respectively and different calcination temperature (1000, 1200 and 1400 ^oC).

   The second step is to prepare the colloid solution by dispersing the produced powder in a polyvinyl alcohol solution (4%) .

Powde

Mn2+ and Ce3+ Doped ZnS nanocrystals were prepared by a simple microwave irradiation method under mild condition. The starting materials for the synthesis of Mn2+ and Ce3+ Doped ZnS P nanocrystals were zinc acetate as zinc source, thioacetamide as a sulfur source, manganese chloride and Cerium chloride as manganese and cerium sources respectively (R & M Chemical) and ethylene glycol as a solvent. All chemicals were analytical grade products and used without further purification. The nanocrystals of Mn2+ and Ce3+ Doped ZnS P with cubic structure were characterized by X-ray powder diffraction (XRD), the morphology of the film is seen by field effect scanning electron microscopy (FESEM). The composition of the samples is analyzed by EDS. The s

Cerium oxide CeO2, or ceria, has gained increasing interest owing to its excellent catalytic applications. Under the framework of density functional theory (DFT), this contribution demonstrates the effect that introducing the element nickel (Ni) into the ceria lattice has on its electronic, structural, and optical characteristics. Electronic density of states (DOSs) analysis shows that Ni integration leads to a shrinkage of Ce 4f states and improvement of Ni 3d states in the bottom of the conduction band. Furthermore, the calculated optical absorption spectra of an Ni-doped CeO2 system shifts towards longer visible light and infrared regions. Results indicate that Ni-doping a CeO2 system would result in a decrease of the band gap. Finally,

This contribution investigates structural, electronic, and optical properties of cubic barium titanate (BaTiO3) perovskites using first-principles calculations of density functional theory (DFT). Generalized gradient approximations (GGA) alongside with PW91 functional have been implemented for the exchange–correlation potential. The obtained results display that BaTiO3 exhibits a band gap of 3.21 eV which agrees well with the previously experimental and theoretical literature. Interestingly, our results explore that when replacing Pd atom with Ba and Ti atoms at 0.125 content a clear decrease in the electronic band gap of 1.052 and 1.090 eV located within the visible range of electromagnetic wavelengths (EMW). Optical parameters such as a