Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

Laser beam has been widely used to improve the mechanical properties of the metals. It used for cutting, drilling, hardening, welding……etc. The use of Laser beam has many features in accuracy and speeding in work, also in the treatment of metals locally, and in the places that is hard to reach by traditional ways. In this research a surface treatment was done to medium carbon steel (0.4%C) which is common kind of steel that is used in industry. Pulsing Neodymium -YAG Laser has been used and 1.06 micrometer wave length and 5 msec and the distance is about 30 centimeter between the exit area of the Laser beam from the system and the piece that treated . We are going to check the fatigue resistance for samples that is

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

In this work, some of new 2-benzylidenehydrazinecarbothioamide derivatives have been prepared by condensation of thiosemicarbazide and different substituted aromatic benzaldehydes in presence of glacial acetic acid to give compounds (1-6), these compounds have characterized by its physical properties and spectroscopic methods. This work also included theoretical study to prove the ability of these compounds as corrosion inhibitors; The program package of Gaussian 09W with its graphical user interface GaussView 5.0 had used for this purpose; the methods of Density Functional Theory (DFT) with basis set of 6-311G (d,p) / hybrid function of B3LYP and semiempirical method of PM3 have been used, the study included theoretical simulation

This study investigates the implementation of Taguchi design in the estimation of minimum corrosion rate of mild-steel in cooling tower that uses saline solution of different concentration. The experiments were set on the basis of Taguchi’s L16 orthogonal array. The runs were carried out under different condition such as inlet concentration of saline solution, temperature, and flowrate. The Signal-to- Noise ratio and ANOVA analysis were used to define the impact of cooling tower working conditions on the corrosion rate. A regression had been modelled and optimized to identify the optimum level for the working parameters that had been founded to be 13%NaCl, 35ᴼC, and 1 l/min. Also a confirmation run to establish the p

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

Cooling towers is one of the most important unit in industry, they are used to dispose heat from cooling media used in the integrated units. The choice of the cooling media plays recently an important rule due to fresh-water scarcity. The use of saline as a cooling media become of growing interest, but the corrosion problem has to be taken in consideration. In this study the simultaneous effect of cooling tower operation parameters on the corrosion rate of mild-steel is considered. The role of NaCl content is found to be pronounced more than the working solution temperature and flowrate. The corrosion of mild-steel in these studied factors had shown an interesting result especially with the NaCl% content. Firstly, there was an increase in t

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result