This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

     The aim of the current study was to investigate endosulfan effects on the Acetylcholinesterase (AChE) enzyme and gene in albino mice. Thirty selected male albino mice were randomly divided into 3 groups. The first group was control group (G1), while the other two treated groups were injected intraperitoneally twice per week with two doses of endosulfanG2 (3 mg/kg) and G3 (17 mg/kg) for 21 and 45 days respectively. The results recorded a significant decrease in AChE enzyme in the group treated with 17 mg/kg b.wt. (3986.67 ±170.32 U/L),compared to the control (5584.33 ±140.35 U/L)and treatment group with 3 mg/kg b.wt.(5556.00 ±341.01) U/L for 21 days. Also, there was a significant decrease in the enzyme level

The aim of this paper is the study of the influence magnetic field on steady state
flows and heat transfer in microchannels between two parallel plates.
It is found that the motion equations are controlled by many dimensionless
parameter, namely magnetic field parameter M Reynolds number Re, physical
quantity at wall W and Knudsen number Kn also found that the energy equations
are controlled by many dimensionless parameter, namely magnetic field parameter
M Reynolds number Re, physical quantity at wall W and Knudsen number Kn ,
Prinkman number Br and Peclet number Pe.
The equations which controlled this type of fluid flow are complicated, so finding
an analytical solution is not easy.
We obtained the velocit

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

This paper investigated the fatigue life behavior of two composite materials subjected to different times of shot peening (2, 4 and 6 min).The first material prepared from unsaturated polyester with E-glass reinforcement by 33% volume fraction. While, the second one was prepared from unsaturated polyester with aluminum powder by2.5% volume fraction. The experimental results showed that the improvement in endurance limit was obtained (for the first material) at 2, 4 and 6 min shot peening times where the percentage of maximum improvement was 25% at shot peening time of 6 min. While, the endurance limit of the second material decreased at shot peening times of 2, 4 and 6 min where the percentage of maximum reduction was 29 % at shot peenin

The inhibitive action of polyvinyl alcohol –sodium nitrite (PVASN) composite on the corrosion of mild steel in simulated cooling water (SCW) has been investigated by weight loss and potentiodynamic polarization. The effect of composite concentration (PVA/SN) , pH, and exposure time on corrosion rate of mild steel were verified using 2 levels factorial design and surface response analysis through weight loss approach, while the electrochemical measurements were used to study the behavior of mild steel in (SCW) with pH between 6 and 8 and in absence and presence of (PVA) in solution containing different concentration of NaNO2. It was verified that all three main variables studied were statistically significant while their interaction is

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Background: The prevention of the enamel demineralization at the periphery of the brackets is a significant challenge to orthodontic professionals. The aim of this clinical study was to compare the Streptococcus mutants count in the plaque surrounding two orthodontic adhesive types, Fuji Ortho LC and Enlight (Ormco). Materials and methods: A total of 13 patients (7 male and 6 female) needing fixed orthodontic appliance therapy were participated. A split mouth technique was followed with appliances bonded by two orthodontic adhesive types, Fuji Ortho LC and Enlight (Ormco). Saliva was collected before placement of appliances (T0) and again at three weeks (T1) and six weeks (T2) after placement of appliances. Plaque was collected from areas a

    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je