The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

Intrusion Detection Systems (IDS) is the main defense mechanism deployed by the current networks to prevent cyber threats. Recurrent Neural Network (RNN) are also a novel IDS structure that replaces the conventional training and testing mechanism. The strategy encodes network traffic data as biological sequences using amino acid codons in such a fashion that the RNN is capable of effectively analyzing temporal and sequence data patterns. RNN architecture design adopts embedding layers to handle codon representations and Long Short-Term Memory (LSTM) layers to perform sequential data learning, which is followed by a fully connected network to perform classification functions, which preserve high feature extraction and classification

This research was conducted to measure the safety of heat stable enterotoxin a (STa) produced by enterotoxigenic Escherichia coli, through studying its toxic effect on human blood lymphocyte, since it showed a promising effect in reducing the proliferation of colorectal cancer cells. the cytogenetic effects of (STa) by using five different concentrations (100, 200, 400, 800 and 1600μg/ml) in comparison with negative (PBS, Phosphate buffer saline) and positive (MMC, Mitomycin C) at concentration of 5μg/ml, controls on human blood lymphocytes obtained from both (10) normal healthy persons and (20) colorectal cancer patients was measured by employing the following parameters: mitotic index, blast index, chromosomal aberrations and micronucle

Pulsed laser deposition (PLD) technique was applied to prepared Chromium oxide (Cr₂O₃) nanostructure doped with Titanium oxide (TiO₂) thin films at different concentration ratios 3,5,7 and 9 wt % of TiO₂. The effect of TiO₂ dopant on the average size of crystallite of the synthesized nanostructures was examined by X-ray diffraction. The morphological properties were discussed using atomic force microscopy(AFM). Observed optical band gap value ranged from 2.68 eV to 2.55 eV by ultraviolet visible(UV-Vis.) absorption spectroscopy with longer wave length shifted  in comparison with that of the bulk Cr₂O₃ ~3eV. This indicated that the synthesized samples a

The influence of sensing element length of no-core fiber strain sensor has been studied and experimentally demonstrated, four different lengths of 125 μm diameter no-core fiber is fused between two standard single-mode fibers and bi-directionally strained, the highest obtained sensitivity was around 16.37 pm με -1 which was exhibited in the shortest no-core fiber segment, to the best of our knowledge this is the first study of the influence of no-core fiber strain sensors length on sensor sensitivity. The proposed sensor can be used in many opto-mechanical applications such as, structural health monitoring, aerospace vehicles and airplane components monitoring.

Zinc oxide (ZnO) nanostructures were synthesized through the hydrothermal method at various conditions growth times (6,7 and 8 hrs.) and a growth temperature (70, 90, and 100 ºC). The prepared ZnO nanostructure samples were described using scanning electron microscopy (SEM) and X-ray diffractometer to distinguish their surface morphologies and crystal structures. The ZnO samples were confirmed to have the same crystal type, with different densities and dimensions (diameter and length). The obtained ZnO nanostructures were used to manufacture gas sensors for NO2 gas detection. Sensing characteristics for the fabricated sensor to NO2 gas were examined at different operating temperatures (180, 200, 220, and 240) ºC with a low gas concentrati

In this work, a Photonic Crystal Fiber (PCF) sensor based on the Surface Plasmon Resonance (SPR) technology was proposed. A thin layer of gold (Au) was deposited on a D-shaped Photonic Crystal Fiber (PCF), which was coated with plasmonic chemically stable gold material with a thickness of 40nm. The performance parameters like sensitivity including wavelength sensitivity and amplitude sensitivity and resolution were evaluated by simulation using COMSOL software. The proposed sensor was created by using the finite element approach, it is numerically examined. The results show that the surface of D-shaped Photonic Crystal Fiber coated with Au behaves as a sensor to detect the refractive index (IR) of toxic metal ions. The impacts of the str