This research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff

 The logistic regression model of the most important regression models a non-linear which aim getting estimators have a high of efficiency, taking character more advanced in the process of statistical analysis for being a models appropriate form of Binary Data.                                                          

Among the problems that appear as a result of the use of some statistical methods I

Background: The dimensional change of alveolar ridge is normal effect of teeth extraction, with unfavourable functional and esthetical outcomes that might jeopardize implant placement. To reduce the biological effects of the dimensional changes of alveolar ridge, various surgical procedures have been recommended, called alveolar ridge preservation. In the previous decade, autogenously teeth have been proposed as bone graft substitution in fresh extraction socket with successful results, yet with various preparation protocols. Aim: Evaluate the formation of new bone derived from the freshly extracted teeth that are grafted immediately in the post extraction sockets, in comparison with sockets without graft filling, by using CBCT and to compa

Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

Abstract Lateral Epicondylitis (LE) which has been referred to as the Tennis Elbow as well is a lesion affecting common tendinous origins of wrist extensors due to chronic overuse injury that results in damaging common extensor tendons which join forearm extensor muscles to humerus. The aim of the present evidence-based clinical statement is reviewing scientific evidences for efficacy of a variety of the rehabilitation methods, chronic lateral epicondylitis management. It is focused upon treating chronic lateral epicondylitis and the latest developments in physiotherapy area for managing chronic lateral epicondylitis. Due to the fact that primary physical impairments in the LE are decreased is the strength of the grip, fundamentally due to

Preparation and Characterization of Maleate, Tartarate,and Phthalate Modified Pectin

Nanofluids, liquid suspensions of nanoparticles (Np), are an effective agent to alter the wettability of oil-wet reservoirs to water-wet thus promoting hydrocarbon recovery. It can also have an application to more efficient carbon storage. We present a series of contact angle (θ) investigations on initially oil-wet calcite surfaces to quantify the performance of hydrophilic silica nanoparticles for wettability alteration. These tests are conducted at typical in-situ high pressure (CO2), temperature and salinity conditions. A high pressure–temperature (P/T) optical cell with a regulated tilted surface was used to measure the advancing and receding contact angles at the desired conditions. The results showed that silica nanofluids can alte

This research studies the effect of adding five different percentages of polymer (2, 4, 6, 8, and 10% of cement weight) on cement mortar's fresh and hardened properties, which was cured at laboratory temperature for 7, 14, and 28 days. Workability increases with increasing polymer. The workability value was lowest (25.6 and 29.4) % in mixtures containing 2% and 4% of (SBR). Increasing polymer ratios significantly decreased mechanical properties (compressive and flexural strength). Therefore, the best results were at 2% SBR and 4% SBR at 28 days of age. An inverse relationship was recorded between the increase in SBR ratios and polymer-modified cement mortar's compressive and flexural strength values. In general, the high