The research aims to derive the efficient industrial plans for Al – shaheed public company under risk by using Target MOTAD as a linear alternative  model for the quadratic programming models.

The results showed that there had been a sort of (trade- off) between risk and the expected gross margins. And if the studied company strives to get high gross margin, it should tolerate risk and vice versa. So the management  of Al- Shaheed Company to be invited to apply the suitable procedures in the production process, in order to get efficient plans that improves it's  performance .

Buffering of Local anaesthesia (LA) has been suggested as a mechanism to improve injection comfort and hasten the onset of anaesthesia. Aim This study aimed to evaluate the effectiveness of buffered LA in the extraction of maxillary premolars and molars. Materials and Methods This randomized controlled study included 100 patients who were indicated for extraction of maxillary posterior teeth, they were randomly divided into two groups; a study group that received infiltration of buffered 2% lidocaine hydrochloride with 1:80,000 epinephrine LA, and a control group that received non-buffered 2% lidocaine hydrochloride with 1:80,000 epinephrine LA. The buffering was performed using the Onset® LA buffering system (Onpharma®). The outcome va

The present study attempts to identify some of the differences between the skull bones of two species Cyprinus carpio and Carassius carassius, which belong to the Cyprinidae family. The study is a taxonomic diagnostic study between the two species which are considered local fish abundant in the Iraqi aquatic environment

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

The artificial intelligence techniques such as neural networks and fuzzy systems play an important role to disconnect flexion & expansion of the swing leg, the earth response force of the other foot has been redesigned. Under that paper, we think the fuzzy controller plan issue for yield following flawed genuine investigation of nonlinear systems. For examination, an essential fuzzy control plot has been bristly developed dependent on a current methodology delegate under the field. In this paper, the Feedforward Neural Network has been implemented with integer, fixed point and floating point data representations. Additionally, The Fuzzy Logic Controllers in both analog and digital forms has been implemented in hardware. Both designs use les

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 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.