All-optical canonical logic units at 40 Gb/s using bidirectional four-wave mixing (FWM) in highly nonlinear fiber are proposed and experimentally demonstrated. Clear temporal waveforms and correct pattern streams are successfully observed in the experiment. This scheme can reduce the amount of nonlinear devices and enlarge the computing capacity compared with general ones. The numerical simulations are made to analyze the relationship between the FWM efficiency and the position of two interactional signals. © 2015 Chinese Laser Press

The possibility of using the magnetic field technique in prevention of forming scales in heat exchangers pipes using
hard water in heat transfer processes, also the studying the effective and controllable parameters on the mechanism of
scale formation.
The new designed heat exchanger experimental system was used after carrying out the basic process designs of the
system. This system was used to study the effect of the temperature (40-90 °C) and water flow rate (0.6-1.2 L/min) on
the total hardness with time as a function of precipitation of hardness salts from water and scale formation.
Different magnetic field designs in the heat exchanger experimental system were used to study the effect of magnetic
field design a

Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

Background: The treatment of dental tissues proceeding to adhesive procedures is a crucial step in the bonding protocol and decides the clinical success ofrestorations. This study was conducted in vitro, with the aim of evaluating thenanoleakage on the interface between the adhesive system and the dentine treated by five surface modalities using scanning electron microscopy and energydispersiveX-ray spectrometry. Materials and methods: Twenty five extracted premolars teeth were selected in the study. Standardized class V cavities were prepared on the buccal and lingual surfaces then the teeth divided into five main groups of (5 teeth in each group n=10) according to the type of dentine surface treatment that was used: Group (A): dentine was

In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably