Optimizing the Access Point (AP) deployment is of great importance in wireless applications owing the requirement to provide efficient and cost-effective communication. Highly targeted by many researchers and academic industries, Quality of Service (QOS) is an important primary parameter and objective in mind along with AP placement and overall publishing cost. This study proposes and investigates a multi-level optimization algorithm based on Binary Particle Swarm Optimization (BPSO). It aims to an optimal multi-floor AP placement with effective coverage that makes it more capable of supporting QOS and cost effectiveness. Five pairs (coverage, AP placement) of weights, signal thresholds, and Received Signal Strength (RSS) measurements simulated with Wireless Insite (WI) software were considered to work in conjunction with the proposed optimization algorithm. Additionally, the AP deployment results obtained from WI and optimization will be compared with the simulation results of the current AP diffusion within the target building. These comparisons will be based on the most important RSS parameters, path loss (PL) and interference. The comparison results showed a significant improvement in RSS and path loss values of (-11.55) dBm and (11.55) dBm. While the interferences are decreased by (7.87 %). Furthermore, the result of performance analysis showed that the proposed algorithm outperforms the current AP deployment by 39.23% in coverage ratio.
The main role of infill drilling is either adding incremental reserves to the already existing one by intersecting newly undrained (virgin) regions or accelerating the production from currently depleted areas. Accelerating reserves from increasing drainage in tight formations can be beneficial considering the time value of money and the cost of additional wells. However, the maximum benefit can be realized when infill wells produce mostly incremental recoveries (recoveries from virgin formations). Therefore, the prediction of incremental and accelerated recovery is crucial in field development planning as it helps in the optimization of infill wells with the assurance of long-term economic sustainabi
Taguchi experimental design (TED) is applied to find the optimum effectiveness of aqueous Red Pomegranate Peel (RPP) extract as a green inhibitor for the corrosion of mild steel in 2M H3PO4 solution. The Taguchi methodology has been used to study the effects of changing, temperature, RPP concentration and contact period, at three levels. Weight-loss measurements were designed by construction a L9 orthogonal arrangement of experiments. Results of the efficiencies of inhibition were embraced for the signal to noise proportion & investigation of variance (ANOVA). The results were further processed with a MINITAB-17 software package to find the optimal condition
... Show MoreThe aim of this study to identify patterns of cerebral control (right and left) for second grade students in the collage of physical education and sports science of the University of Baghdad, as well as identify the definition of theThe Effect of Using the Bybee Strategy(5ES) according to Brain Control Patterns in Learning a Kinetic Series on Floor exercises in Artistic Gymnastics for menمجلة الرياضة المعاصرةالمجلد 19 العدد 1 عام 2020effect using the (Bybee) strategy (5ES) according to brain control patterns inlearning a Kinetic series on floor exercises In artistic gymnastics for men, andidentify the best combination between the four research groups learn, use Finderexperimental method research sample consi
... Show MoreIn this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and
... Show MoreElectronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene
... Show MoreIn the present work, Response Surface Methodology (RSM) was utilized to optimize process variables and find the best circumstances for indirect electrochemical oxidation of mimicked wastewater to remove phenol contaminants using prepared ternary composite electrode. The electrodeposition process is used for the synthesis of a ternary composite electrode of Mn, Co, and Ni oxides. The selected concentrations of metal salts of these elements were 0.05, 0.1, and 1.5 M, with constant molar ratio, current density, and electrolysis time of 1:1:1, 25 mA/cm2, and 2 h. Interestedly, the gathered Mn-Co-Ni oxides were deposited at both the anode and cathode. X-ray diffraction (XRD) and scanning electron microscopy (SEM) facilitated the qualitative char
... Show MoreNurse scheduling problem is one of combinatorial optimization problems and it is one of NP-Hard problems which is difficult to be solved as optimal solution. In this paper, we had created an proposed algorithm which it is hybrid simulated annealing algorithm to solve nurse scheduling problem, developed the simulated annealing algorithm and Genetic algorithm. We can note that the proposed algorithm (Hybrid simulated Annealing Algorithm(GS-h)) is the best method among other methods which it is used in this paper because it satisfied minimum average of the total cost and maximum number of Solved , Best and Optimal problems. So we can note that the ratios of the optimal solution are 77% for the proposed algorithm(GS-h), 28.75% for Si
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Hexapod robot is a flexible mechanical robot with six legs. It has the ability to walk over terrain. The hexapod robot look likes the insect so it has the same gaits. These gaits are tripod, wave and ripple gaits. Hexapod robot needs to stay statically stable at all the times during each gait in order not to fall with three or more legs continuously contacts with the ground. The safety static stability walking is called (the stability margin). In this paper, the forward and inverse kinematics are derived for each hexapod’s leg in order to simulate the hexapod robot model walking using MATLAB R2010a for all gaits and the geometry in order to derive the equations of the sub-constraint workspaces for each
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