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

Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

The river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids. So, the water salinity impact of the river is one of the major factors effects of water quality. Tigris river water salinity increase with streamline and time due to the decrease in the river flow and dam construction from neighboring countries. The major objective of this research to developed salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plant along Tigris River in Baghdad city using artificial neural network model (ANN). The parameter used in a model built is (Turbidity, Ec, T.s, S.s, and TDS in)

Animal fats are a good, promising and ethical alternative source for biodiesel production, but they need more complex treatments than vegetable oils. Iraqi butchery plants waste fats (sheep fat) which are suggested as feedstock to produce biodiesel. This type of fat contains a large quantity of free fatty acids (FFAs) (acid number 49.13 mg KOH/g of fat). The direct transesterification of such fats produce high amount of soap instead of desired biodiesel, so a pre-treatment step (to reduce FFAs) is necessary before transesterification. This step was done by esterification of the free fatty acids in the fat by adding ethanol and using 1% acid catalyst (H2SO4) for 30 minutes. The results showed that the acid number of sheep fat after pre-tr

This study is designed to isolate and molecular identification of C. gattii, C. gattii is pathogenic yeast and effect immunocomposed and immunocompetent, Methods: collect 50 samples from eucalyptus leaves. The collection time was extended from November 2021 to February 2022 and then culture at SDA, Cryptococcus Differential Agar esculin agar and Eucalyptus leaves agar, Brain heart infusion agar with methyldopa and Brain heart infusion agar with methyldopa media, biochemical test including urease test, and then confirm identification by molecular identification by PCR technique sequencing and genetic analysis. The results showed that 4 swaps taken from eucalyptus leaves included cryptococcus neoformans. This study indicated that the virulenc

This study was aimed to one of the most prevalent causes for endodontic treatment failure is the presence of Enterococcus faecalis bacterium within teeth root canals. To achieve successful treatment, it is so important to study E. faecalis behavior. The aim of study was to investigate biofilm production and antibiotic sensitivity of E. faecalis isolated from root canals. Results showed isolation of E. feacalis (65%) of samples, identified by specific gene by PCR technique. Most isolates were sensitive to Imipenem and resistant to Erythromycin, Clindamycin, Tetracycline and Trimethoprim. Strong biofilm production was detected among 29.5% of highest antibiotic resistant isolates. The results may indicate that infected root canals with E. feac