In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

The effect of three high temperatures for five exposure periods on the developments of larvae, pupae and adults of Trogoderma granarium (Everts) and their biological performance were investigated. The results revealed that the percent of mortality was increased as the temperature and the exposure period increased, e. g. exposing last instar larvae to 45°C for 6 hrs caused 100% death of this stage, while exposing adults (1-3) days old to the same temperature and exposure time resulted in that these adults did not able to survive more than 24 hrs.; in addition, the results showed that the ability of reproduction of adults was depended on the temperature, duration of exposure and the sex.

ABSTRACTBackground : Acne vulgaris is a
common skin disease, affecting more than 85% of
adolescents and often continuing into adulthood.
People between 11 and 30 years of age and up to
5% of older adults. For most patients acne remains
a nuisance with occasional flares of unsightly
comedones, pustules and nodules. For other less
fortunate persons, the sever inflammatory response
to Propionibacterium acnes (P.acnes) results in
permanent
Methods: Disfiguring scars. (1, 2) Stigmata of sever
acne cane lead to social ostracism, withdrawal
from society and severe psychologic
depression (1-4).
Result Pathogenesis of acne Traditionally, acne
has been thought of as a multifactorial disease of
the fo

In addition to the primary treatment, biological treatment is used to reduce inorganic and organic components in the wastewater. The separation of biomass from treated wastewater is usually important to meet the effluent disposal requirements, so the MBBR system has been one of the most important modern technologies that use plastic tankers to transport biomass with wastewater, which works in pure biofilm, at low concentrations of suspended solids. However, biological treatment has been developed using the active sludge mixing process with MBBR. Turbo4bio was established as a sustainable and cost-effective solution for wastewater treatment plants in the early 1990s and ran on minimal sludge, and is easy to maintain. This

An agricultural waste (walnut shell) was undertaken to remove Cu(II) from aqueous solutions in batch and continuous fluidized bed processes. Walnut shell was found to be effective in batch reaching 75.55% at 20 and 200 rpm, when pH of the solution adjusted to 7. The equilibrium was achieved after 6 h of contacting time. The maximum uptake was 11.94mg/g. The isotherm models indicated that the highest determination coefficient belongs to Langmuir model. Cu (II) uptake process in kinetic rate model followed the pseudo-second-order with determination coefficient of 0.9972. More than 95% of the Cu(II) were adsorbed on the walnut shells within 6 h at optimum agitation speed of 800 rpm. The main functional groups responsible for biosorption of

In this paper a stirred-bed performed of the copper catalyzed synthesis of ethylchlorosilanes from silicon and ethyl chloride was described. A Si-catalyst mixture prepared by reaction of CuCl and Si was employed. The compositions of products were mainly ethyltrichlorosilane, diethyldichlorosilane, and ethyldichlorosilane and mainly depended on the extent of Cu in the mixture and the reaction temperature. A promoting effect on the extent of adsorption was observed on the addition of certain additives. The kinetic data revealed the direct depended of the reaction rate on C2H5Cl pressure.

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices