This work was conducted to study the ability of locally prepared Zeolite NaY for the reduction of sulfur compounds from Iraqi natural gas by a continuous mode adsorption unit. Zeolite Y was hydrothermally synthesized using abundant kaolin clay as aluminum precursor. Characterization was made using chemical analysis, XRD and BET surface area. Results of the adsorption experiments showed that zeolite Y is an active adsorbent for removal H2S from natural gas and other gas streams. The effect of temperature was found inversely related to the removal efficiency. Increasing bed height was found to increase the removal efficiency at constant flow rate of natural gas. The adsorption capacity was evaluated and its maximum uptake was 5.345 mg H2S/g z

   A new nano-sized NiMo/TiO₂-γ-Al₂O₃ was prepared as a Hydrodesulphurization catalyst for Iraqi gas oil with sulfur content of 8980 ppm, supplied from Al-Dura Refinery. Sol-gel method was used to prepare TiO₂- γ-Al₂O₃ nano catalyst support with 64% TiO_2, 32% Al₂O₃, Ni-Mo/TiO-γ-Al₂O₃ catalyst was prepared under vacuum impregnation conditions to loading metals with percentage 3.8 wt.% and 14 wt.% for nickel and molybdenum respectively while the percentage for alumina, and titanium became 21.7, and 58.61 respectively. The synthesized TiO₂- γ-Al₂O₃ nanocomposites and Ni-Mo /TiO₂

This work represents the set of measurements of radon and thoron concentrations levels of soil-gas in Al-Kufa city in Iraq using electric Radon meter (RAD-7). Radon and thoron concentration were measured in soil-gas in 20 location for three depth of (50, 100 and 150) cm.
The results show that the emanation rate of radon and thoron gas varied from location to anther, depending on the geological formation. The Radon concentration in soil has been found to vary from (12775±400) Bq/m3 at 150 cm depth in location (sample K2) to (41.45±17) Bq/m3, for depth 150 cm in location (sample K20). The thoron concentration in soil has been found to vary from (198±8.5) Bq/m3 at 150 cm depth in location samples (K1 & K2) to undetected in the mos

The faujasite type Y zeolite catalyst was prepared from locally available kaolin. For prepared faujasite type NaY zeolite X-ray, FT-IR, BET pore volume and surface area, and silica/ alumina were determined. The Xray and FT-IR show the compatibility of prepared catalyst with the general structure of standard zeolite Y. BET test shows that the surface area and pore volume of prepared catalyst were 360 m2 /g and 0.39 cm3 /g respectively.
The prepared faujasite type NaY zeolite modified by exchanging sodium ion with ammonium ion using ammonium nitrate and then ammonium ion converted to hydrogen ion. The maximum sodium ion exchange with ammonium ion was 53.6%. The catalytic activity of prepared faujasite type NaY, NaNH4Y and NaHY zeolites

In this paper, a simulation of the electrical performance for Pentacene-based top-contact bottom-gate (TCBG) Organic Field-Effect Transistors (OFET) model with Polymethyl methacrylate (PMMA) and silicon nitride (Si3N4) as gate dielectrics was studied. The effects of gate dielectrics thickness on the device performance were investigated. The thickness of the two gate dielectric materials was in the range of 100-200nm to maintain a large current density and stable performance. MATLAB simulation demonstrated for model simulation results in terms of output and transfer characteristics for drain current and the transconductance. The layer thickness of 200nm may result in gate leakage current points to the requirement of optimizing the t

This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

Optimizing the Access Point (AP) deployment has a great role in wireless applications due to the need for providing an efficient communication with low deployment costs. Quality of Service (QoS), is a major significant parameter and objective to be considered along with AP placement as well the overall deployment cost. This study proposes and investigates a multi-level optimization algorithm called Wireless Optimization Algorithm for Indoor Placement (WOAIP) based on Binary Particle Swarm Optimization (BPSO). WOAIP aims to obtain the optimum AP multi-floor placement with effective coverage that makes it more capable of supporting QoS and cost-effectiveness. Five pairs (coverage, AP deployment) of weights, signal thresholds and received s