Research summarized in applying the model  of fuzzy goal programming for aggregate production planning , in General Company for hydraulic industries / plastic factory to get an optimal production plan  trying to cope with the impact that fluctuations in demand and  employs all available resources using two strategies where they are available   inventories  strategy and  the strategy of  change in the level of the workforce, these   strategies  costs are usually imprecise/fuzzy. The plant administration trying to minimize total production costs, minimize carrying costs and minimize changes in labour levels. depending on the gained data from th

         Let R be a commutative ring , the pseudo – von neuman  regular graph of the ring R is define as a graph whose vertex set consists of all elements of R and any two distinct vertices a and b are adjacent if and only if   , this graph denoted by P-VG(R) ,  in this work we got some new results a bout chromatic number of  P-VG(R).

The operation of production planning is a difficult operation and it's required High effect and large time especially it is dynamic activity which it's basic variables change in continuous with the time, for this reason it needs using one of the operation research manner (Dynamic programming) which has a force in the decision making process in the planning and control on the production and its direct affect on the cost of production operation and control on the inventory.

This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward

     This study aims to build a wireless computer network for a large company or university to enhance mobility and allow university users to stay connected at any time or place, which is achieved by applying the Universal Interoperability for Microwave Access (WiMax) technology. WiMax is based on the 802.16 sets of standards and has the most efficient and advanced hardware capabilities to meet the demands of teachers and students to browse the web or download files quickly. OPNET Modeler version 14.5 was used to determine the quality of service parameters of WiMax.

A new Turbidimetric method characterized by simplicity, accuracy and speed for determination of Hydronium ion by continuous flow injection analysis. The method was based on the formation of complex Zn3[Fe(CN)6] for Zinc(II) that was eluted by Hydronium ion from cation exchanger column with Potassium hexacyanoferrate(III) for the formation of a pale yellow precipitate and this precipitate was determined using homemade Linear Array Ayah-5SX1-T-1D continuous flow injection analyser. The optimum parameters were 2.7 mL.min-1 flow rate using H2O as a carrier stream, 1.7 mL.min-1 reagent stream, 110 L sample volume and open valve for the purge of the sample segment. Data treatment shows that linear range 0.01-0.1 mol.L-1 for each acids (HClO

A new Turbidimetric method characterized by simplicity, accuracy and speed for determination of Hydronium ion by continuous flow injection analysis. The method was based on the formation of complex Zn3[Fe(CN)6] for Zinc(II) that was eluted by Hydronium ion from cation exchanger column with Potassium hexacyanoferrate(III) for the formation of a pale yellow precipitate and this precipitate was determined using homemade Linear Array Ayah-5SX1-T-1D continuous flow injection analyser. The optimum parameters were 2.7 mL.min-1 flow rate using H2O as a carrier stream, 1.7 mL.min-1 reagent stream, 110 L sample volume and open valve for the purge of the sample segment. Data treatment shows that linear range 0.01-0.1 mol.L-1 for each acids (HClO

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database