This research shows the experimental results of the bending moment in a flexible and rigid raft foundation rested on dense sandy soil with different embedded depth throughout 24 tests. A physical model of dimensions (200mm*200mm) and (320) mm in height was constructed with raft foundation of (10) mm thickness for flexible raft and (23) mm for rigid raft made of reinforced concrete. To imitate the seismic excitation shaking table skill was applied, the shaker was adjusted to three frequencies equal to (1Hz,2Hz, and 3Hz) and displacement magnitude of (13) mm, the foundation was located at four different embedment depths (0,0.25B = 50mm,0.5B = 100mm, and B = 200mm), where B is the raft width. Generally, the maximum bending

This paper presents an improved technique on Ant Colony Optimization (ACO) algorithm. The procedure is applied on Single Machine with Infinite Bus (SMIB) system with power system stabilizer (PSS) at three different loading regimes. The simulations are made by using MATLAB software. The results show that by using Improved Ant Colony Optimization (IACO) the system will give better performance with less number of iterations as it compared with a previous modification on ACO. In addition, the probability of selecting the arc depends on the best ant performance and the evaporation rate.

One of the most essential components of asphalt pavements is the filler. It serves two purposes. First, this fine-grained material (diameter less than 0.075 mm) improves the cohesiveness of aggregate with bitumen. Second, produce a dense mixture by filling the voids between the particles. Aluminum dross (AD), which is a by-product of aluminum re-melting, is formed all over the world. This material causes damage to humans and the environment; stockpiling AD in landfills is not the best solution. This research studies the possibility of replacing part of the conventional filler with aluminum dross. Three percent of dross was used, 10, 20, and 30% by filler weight. The MarshallMix design method was adopted to obtain the op

Background: Oocytes are susceptible to alterations in the various fatty acid contents of follicular fluid (FF), which may influence maturation and embryogenesis. Different fatty acids exert various effects on intracytoplasmic sperm injection (ICSI), which needs further studies to uncover the involved mechanisms. Objectives: To assess FF fatty acids in women undergoing ICSI and to correlate them with ICSI parameters, namely the total count of aspirated oocytes, oocyte maturation rate, fertilization rate and percentage of good-quality embryos. Methods: Fifty women undergoing ICSI were enrolled in this cross-sectional study. FF samples were collected during oocyte retrieval and were analyzed for fatty acids using gas chromatography. Fa

In this work, an inventive photovoltaic evaporative cooling (PV/EC) hybrid system was constructed and experimentally investigated. The PV/EC hybrid system has the prosperous advantage of producing electrical energy and cooling the PV panel besides providing cooled-humid air. Two cooling techniques were utilized: backside evaporative cooling (case #1) and combined backside evaporative cooling with a front-side water spray technique (case #2). The water spraying on the front side of the PV panel is intermittent to minimize water and power consumption depending on the PV panel temperature. In addition, two pad thicknesses of 5 cm and 10 cm were investigated at three different water flow rates of 1, 2, and 3 lpm. In Case #1,

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

Rheumatoid arthritis is a chronic, progressive, inflammatory autoimmune disease of unidentified etiology, associated with articular, extra-articular and systemic manifestation that require long-standing treatment. Taking patient’s beliefs about the prescribed medication in consideration had been shown to be an essential factor that affects adherence of the patient in whom having positive beliefs is an essential for better adherence. The purpose of the current study was to measure beliefs about medicines among a sample of Iraqi patients with Rheumatoid arthritis and to determine possible association between this belief and some patient-certain factors. This study is a cross-sectional study carried out on 250 already diagnosed rheumatoid