The monitoring weld quality is increasingly important because great financial savings are possible because of it, and this especially happens in manufacturing where defective welds lead to losses in production and necessitate time consuming and expensive repair. This research deals with the monitoring and controllability of the fusion arc welding process using Artificial Neural Network (ANN) model. The effect of weld parameters on the weld quality was studied by implementing the experimental results obtained from welding a non-Galvanized steel plate ASTM BN 1323 of 6 mm thickness in different weld parameters (current, voltage, and travel speed) monitored by electronic systems that are followed by destructive (Tensile and Bending) and non

Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

In this study, the dynamic modeling and step input tracking control of single flexible link is studied. The Lagrange-assumed modes approach is applied to get the dynamic model of a planner single link manipulator. A Step input tracking controller is suggested by utilizing the hybrid controller approach to overcome the problem of vibration of tip position through motion which is a characteristic of the flexible link system. The first controller is a modified version of the proportional-derivative (PD) rigid controller to track the hub position while sliding mode (SM) control is used for vibration damping. Also, a second controller (a fuzzy logic based proportional-integral plus derivative (PI+D) control scheme) is developed for both vibra

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

In this work , a hybrid scheme tor Arabic speech for the recognition

of  the speaker  verification  is presented  . The scheme is hybrid as utilizes the traditional digi tal signal processi ng and neural network . Kohonen neural  network has been used as a recognizer  tor speaker verification after extract spectral  features from an acoustic signal  by Fast Fourier Transformation Algorithm(FFT) .

The system was im plemented using a PENTIUM  processor , I000

MHZ compatible and MS-dos 6.2 .

The robot arm is the most popular robotic form used in industry. Thus, it is crucial to make a system programming which could controlled the movement of each part in the industrial robot to make it works properly. One of the simplest models of the robot arm is EDARM ED-7100 which has a controller to control the movement of the robot arm manually. In this study, the robot controller has been redesigned in order to improve this robot's function. The new controller system used AT89S52 microcontroller which has wire connected to the robot hand. A function has been added with this controller to improve the system of controlling and becomes better than the previous system (only manually). The functions of the new system include three mo

The activity of Adhatoda vasica crude plants extracts against B.thuringiensis bacteria was determined by MIC test and sensitivity test which showed no response of this type of bacteria against extracts .The interference between the effect of hot and cold aqueous extracts and Bacillus thuringiensis bacteria for controlling the population of fig moth when males and females released before treatment under control condithion was gave a highly percentage of larval mortality which reached to 100% in (B.t. + hot aqueous extract ) and 97.3% in (B.t + coldaqueous extract ) after two weeks of treatment when concentration of 50% of aqueous extracts and 5×10?1of Bacillus thuringiensis bacteria but when the insect (males & females) released after