The study aims to identify the metamemory and perceptual speed among College students, the correlation between metamemory and perceptual speed among College students, and to which extend does metamemory contribute to perceptual speed among College students. The sample consisted of group of students were selected randomly by the researcher from five-different disciplines at the college of education for pure sciences. To collect study data, the researcher utilized two scales: perceptual speed scale that has translated to Arabic language by (Al-Shraqawi, Al- Shaikh, and Nadia Abed Al-Salam (1993). The second scale is metamemory scale (2002) which has translated to Arabic by Abu Ghazal (2007). The results revealed that college students have

Dielectric measurements were carried on pure and doping potassium sulfate with copper and iron ions samples at 1wt.% and 3wt.% for both of copper and iron. The dielectric constant (ε') decreases exponentially from 2.8 to 1.5 as frequency increase for both dopant which is attributed to the space charge and structural distortion. The dielectric loss (ε") for Cu dopant decrease gradually with frequency. The same behavior for 1%Fe dopant while its 3%Fe doping started from 0.27 then decrease exponential. Band gaps for all samples almost constant around 6 eV.

When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

Objective Advantageous properties of silicone elastomer made it one of the favorable materials in maxillofacial prosthesis construction, but these properties may change after months of usage or after pigments addition. This study aimed to define the optimum concentration for a mixture of two types of intrinsic pigments that added to VST-50 maxillofacial silicone material and study their effects on mechanical properties before and after artificial aging. Methods After the pilot study was conducted, 0.1% by weight of rayon flocking and 0. 2% by weight of burnt sienna intrinsic pigment concentration was selected because of improvement in tested mechanical properties of VST-50 maxillofacial silicone. A total of one hundred and eighty samples we