Abstract

This research aims to design a multi-objective mathematical model to assess the project quality based on three criteria: time, cost and performance. This model has been applied in one of the major projects formations of the Saad Public Company which enables to completion the project on time at an additional cost that would be within the estimated budget with a satisfactory level of the performance which match with consumer requirements. The problem of research is to ensure that the project is completed with the required quality Is subject to constraints, such as time, cost and performance, so this requires prioritizing multiple goals. The project

Throughout Agriculture has mostly relied on the use of natural fertilizers throughout human history, which are compounds that increase the nitrogen levels in the soil. Modern agriculture was made possible by the introduction of synthetic fertilizers at the end of the 19th centuryproduction of agriculture. Their application enhanced crop yields and sparked an agricultural revolution unlike anything the world had ever seen.In the near future, synthetic fertilizers are anticipated to continue to have a significant impa ct on human life, both positively and negatively. They are frequently utilized for producing all t ypes of crops and are essential to plant growth. The significance of synthetic fertilizers is their ability to provide the soil w

ABSTRACT

            The controversy is currently revolving around industrial additives, including antioxidants, their negative effects on consumer health and the emergence of various and various diseases, which led scientists and researchers to intensify most studies on natural antioxidants and their synthesis from medicinal plants mentioned in ancient medicine and in divine books as potential antioxidants of increasing importance. Therefore, this study was designed to synthesize silver nitrate particles from plant leaf extracts (Figs, Olives, and Moringa) and study their effect on bacterial inhibition of each of the undesirable Coliform bacteria (E-Coli,

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.