The first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o

The first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o

In this work, a single pile is physically modeled and embedded in an upper liquefiable loose sand layer overlying a non-liquefiable dense layer. A laminar soil container is adopted to simulate the coupled static-dynamic loading pile response during earthquake motions: Ali Algharbi, Halabjah, El-Centro, and Kobe earthquakes. During seismic events with combined loading, the rotation along the pile, the lateral and vertical displacements at the pile head as well as the pore pressure ratio in loose sandy soil were assessed. According to the experimental findings, combined loading that ranged from 50 to 100% of axial load would alter the pile reaction by reducing the pile head peak ground acceleration, rotation of the pile, and lateral displacem

Cold plasma is a relatively low temperature gas, so this feature enables us to use cold plasma to treat thermally sensitive materials including polymers and biologic tissues. In this research, the non-thermal plasma system is designed with diameter (3 mm, 10 mm) Argon at atmospheric pressure as well as to be suitable for use in medical and biotechnological applications.
The thermal description of this system was studied and we observed the effect of the diameter of the plasma needle on the plasma, when the plasma needle slot is increased the plasma temperature decrease, as well as the effect of the voltages applied to the temperature of the plasma, where the temperature increasing with increasing the applied voltage . Results showed t

This study has been undertaken to postulate the mechanism of impact test at low velocities. Thin-walled tubes of 100Cr6 were deformed under axial compression. In the present work there are seven velocities (4.429,4.652,5.240,5.600,5.942,6.264, 6.569) m\sec were applied to show how they effect the load, change in length, also the kinetic energy. However, the comparison between the obtained results and the other studies (Alexandar[3] , Abramowicz[4], Ayad[5]) was made the present work and Ayad data show good agreement. Load, change in length, kinetic energy were determined to understand the impact test.

Single long spiral tube column pressure swing adsorption (PSA) unit, 25 mm diameter, and 6 m length was constructed to study the separation of water from ethanol at azeotropic concentration of 95 wt%. The first three meters of the column length acted as a vaporizer and the remaining length acted as an adsorber filled by commercial 3A zeolite. The effect of pressure, temperature and feed flow rate on the product ethanol purity, process recovery and productivity were studied. The results showed that ethanol purity increased with temperature and pressure and decreased with feed flow rate. The purity decreased with increasing productivity. The purity range was 98.9 % to 99.6 %, the recovery range was 0.82 to 0.92 and the productivity range w