The Hopfield network is one of the easiest types, and its architecture is such that each neuron in the network connects to the other, thus called a fully connected neural network. In addition, this type is considered auto-associative memory, because the network returns the pattern immediately upon recognition, this network has many limitations, including memory capacity, discrepancy, orthogonally between patterns, weight symmetry, and local minimum. This paper proposes a new strategy for designing Hopfield based on XOR operation; A new strategy is proposed to solve these limitations by suggesting a new algorithm in the Hopfield network design, this strategy will increase the performance of Hopfield by modifying the architecture of t

   A low-cost, RGB LED-based visible-light spectrophotometer was designed to measure dyes concentration. Dyes are widely used as indicators or coloring agents in different applications and knowing their concentration is an essential part for many studies. The proposed spectrophotometer provides many functionalities that clones the traditional expensive spectrophotometers for a budged price under $50. It was aimed to provide a versatile tool for instructors and educators to teach their students the fundamental concepts behind spectrophotometry. Malachite green, methyl red, and methyl orange dyes were chosen to be good samples to show the integrity of the proposed spectrophotometer in terms of accuracy, repeatability, and sensitivity as

The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.

wind load coefficient

The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD).  In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc

تم تحضير ثلاث معقدات جديدة Ni (II)و Cu (II) و Zn (II) باستخدام الليكند المحضر الجديد من تفاعل حامض مالونيك ثنائي هيدرازايد مع 2-بيريدين كربوكسالديهايد. حيث شخصت المعقدات لمحضرة وكذلك الليكند باستخدام تقنيات مختلفة مثل FT-IR و UV-Vis و Mass و 1H-NMR و 13C-NMR وتحليل العناصر CHN و تقدير محتوى  الكلور والموصلية المولارية والحساسية المغناطيسية والامتصاص الذري لتشخيص هذه المركبات. لكل معقد محضر جديد من النيكل والنحاس والزنك ، كشفت نتائج ا