Robots have become an essential part of modern industries in welding departments to increase the accuracy and rate of production. The intelligent detection of welding line edges to start the weld in a proper position is very important. This work introduces a new approach using image processing to detect welding lines by tracking the edges of plates according to the required speed by three degrees of a freedom robotic arm. The two different algorithms achieved in the developed approach are the edge detection and top-hat transformation. An adaptive neuro-fuzzy inference system ANFIS was used to choose the best forward and inverse kinematics of the robot. MIG welding at the end-effector was applied as a tool in this system, and the wel

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Robots have become an essential part of modern industries in welding departments to increase the accuracy and rate of production. The intelligent detection of welding line edges to start the weld in a proper position is very important. This work introduces a new approach using image processing to detect welding lines by tracking the edges of plates according to the required speed by three degrees of a freedom robotic arm. The two different algorithms achieved in the developed approach are the edge detection and top-hat transformation. An adaptive neuro-fuzzy inference system ANFIS was used to choose the best forward and inverse kinematics of the robot. MIG welding at the end-effector was applied as a tool in this system, and the wel

Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

Polyaniline nanofibers (PAni-NFs) have been synthesized under various concentrations (0.12, 0.16, and 0.2 g/l) of aniline and different times (2h and 3 h) by hydrothermal method at 90°C. Was conducted with the use of X-ray diffraction (XRD), Fourier Transform Infrared spectra (FTIR), Ultraviolet-Visible (UV-VIS) absorption spectra, Thermogravimetric Analysis (TGA), and Field Emission-Scanning Electron Microscopy (FE-SEM). The X-ray diffraction patterns revealed the amorphous nature of all the produced samples. FE-SEM demonstrated that Polyaniline has a nanofiber-like structure. The observed typical peaks of PAni were (1580, 1300-1240, and 821 cm-1 ), analyzed by the chemical bonding of the formed PAni through FTIR spectroscopy. Also, tests

The subject of an valuation of quality of construction projects is one of the topics which it becomes necessary of the absence of the quantity standards in measuring the control works and the quality valuation standards in constructional projects. In the time being it depends on the experience of the workers which leads to an apparent differences in the valuation.

The idea of this research came to put the standards to evaluate the quality of the projects in a special system depending on quantity scale nor quality specifying in order to prepare an expert system “ Crystal “ to apply this special system to able the engineers to valuate the quality of their projects easily and in more accurate ways.

The varied applications of polystyrene in various fields of life led to examining the cause of radiation influence on some rheological behavior of commercial Polystyrene (PS) solution in the chloroform (CHCl3) solvent. Polystyrene grains shape samples were irradiated using the radioactive element Cesium- 137 with (9 µci) activity for 10, 20, and 30 minutes. The viscosity of the polymer solution depends on the concentration and size (i.e. molecular weight) of the dissolved polymer. Experimental data showed that the radiation dose affected the value of viscosity (shear, relative, specific, and reduced). The viscosity value significantly reduced at 10 min radiation dose and when increasing the dose, the viscosity value increased