The aim of this research is to design and construct a
semiconductor laser range finder operating in the near infrared range
for ranging and designation. The main part of the range finder is the
transmitter which is a semiconductor laser type GaAs of wavelength
0.904 μm with a beam expander and the receiver; a silicon pin
detector biased to approve the fast response time with it's collecting
optics. The transmitters pulse width was 200ns at a threshold current
of 10 Ampere and maximum operating current of 38 Ampere. The
repetition rate was set at 660Hz and the maximum operating output
power was around 1 watt. The divergence of the beam was 0.268o
the efficiency of the laser was 0.03% at a duty cycle of 1.32x

One of the most important techniques for preparing nanoparticle material is Pulsed Laser Ablation in Liquid technique (PLAL). Carbon nanoparticles were prepared using PLAL, and the carbon target was immersed in Ultrapure water (UPW) then irradiated with Q-switched Nd:YAG laser (1064 nm) and six ns pulse duration. In this process, an Nd:YAG laser beam was focused near the carbon surface. Nanoparticles synthesized using laser irradiation were studied by observing the effects of varying incident laser pulse intensities (250, 500, 750, 1000) mJ on the particle size (20.52, 36.97, 48.72, and 61.53) nm, respectively. In addition, nanoparticles were characterized by means of the Atomic Force Microscopy (AFM) test, pH easurement

Background: Color stability of glass ionomers (GIs) could be affected by many factors such as pH and consumption of liquid medications like antibiotics. Most common antibiotics used during childhood are amoxicillin suspension (AM.S) and azithromycin suspension (AZ.S) which have acidic and basic pH respectively. Aim: to evaluate and compare the effect of AM.S and AZ.S on color stability of nano resin-modified GI. Methods: Thirty disc of nano resin-modified glass ionomer (2mm height x 4mm diameter) were divided into three groups (n=10 for each) and independently exposed to AM.S, AZ.S, and artificial saliva (A.S.). Color stability was evaluated in triplicate by VITA Easyshade® before and after three immersion protocols, repeated over a thr

Background: Color stability of glass ionomers (GIs) could be affected by many factors such as pH and consumption of liquid medications like antibiotics. Most common antibiotics used during childhood are amoxicillin suspension (AM.S) and azithromycin suspension (AZ.S) which have acidic and basic pH respectively. Aim: to evaluate and compare the effect of AM.S and AZ.S on color stability of nano resin-modified GI. Methods: Thirty disc of nano resin-modified glass ionomer (2mm height x 4mm diameter) were divided into three groups (n=10 for each) and independently exposed to AM.S, AZ.S, and artificial saliva (A.S.). Color stability was evaluated in triplicate by VITA Easyshade® before and after three immersion protocols, repeated over

Receipt date:12/7/2020 accepted date:24/1/2021 Publication date:31/12/2021

  This work is licensed under a Creative Commons Attribution 4.0 International License.

The constant characteristic of international relations is the constant change due to political, economic and military developments in addition to technology, and this in turn has led to many transformations in the concept of power, its uses, and the elements that form power and its distribution, and according to those variables, the concept of power has shifted from hard to soft, up to smart powe

Background: Recent studies suggest that chronic periodontitis (CP) and type2 diabetes mellitus (T2DM) are bidirectionally associated. Analysis of saliva as a mirror of oral and systemic health could allow identification of α amylase (α-Am) and albumin (A1) antioxidant system markers to assist in the diagnosis and monitoring of both diseases. The present study aims at comparing the clinical periodontal parameters in chronic periodontitis patients with poorly or well controlled Type 2Diabetes Mellitus, salivary α-Am, A1, flow rate (FR) and pH then correlate between biochemical, physical and clinical periodontal parameters of each study and control groups. Materials and Methods: 80 males, with an age range of (35-50) years were divide

Background: Periodontitis (PD) is well-known chronic disease affecting the periodontal ligament and alveolar bone, Osteoarthritis (OA) is a chronic joint disease with compound reasons characterized by synovial inflammation, subchondral bone remodeling, also the formation of osteophytes, that cause cartilage degradation. Chronic periodontitis and osteoarthritis are considered widely prevalent diseases and related to tissue destruction due to chronic inflammation in general health and oral health. The aim of this study is todetermine the association of chronic periodontitis and osteoarthritits in patients by analysing tumor necrosis factor alpha TNFα and high sensitive c-reactive protein (hsCRP) in the serum. Materials and Method: A tot

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

: Sound forecasts are essential elements of planning, especially for dealing with seasonality, sudden changes in demand levels, strikes, large fluctuations in the economy, and price-cutting manoeuvres for competition. Forecasting can help decision maker to manage these problems by identifying which technologies are appropriate for their needs. The proposal forecasting model is utilized to extract the trend and cyclical component individually through developing the Hodrick–Prescott filter technique. Then, the fit models of these two real components are estimated to predict the future behaviour of electricity peak load. Accordingly, the optimal model obtained to fit the periodic component is estimated using spectrum analysis and Fourier mod

Image Fusion Using A Convolutional Neural Network