Micro wind turbines are generally used in remote locations, and it is difficult and expensive to repair faults which forced the need for condition monitoring and fault diagnosis which has not been used extensively for small turbines. The possibility of utilizing Fast Fourier Transform (FFT) for diagnosis the faults of broken rotor bar in squirrel cage induction motor of a micro wind turbine was investigated. Monitoring and analysis the current spectrum can be effective for diagnosis the early stage of faults and avoid complete catastrophic failure in the motor by powerful virtual instruments and LabVIEW software as an integral part of this instrumentation. Combination advanced signal processing technique with computerized signal processi

AIM: To determine the value of the combination of thin-section 3 mm ‎coronal and standard ‎axial DWI and their impact in facilitating the diagnosis of ‎‎acute brainstem infarction. METHODS: A cross-sectional study conducted from the 1st of April 2017 to the end of February 2018 on 100 consecutive patients (66% were male, and 34% were female) with isolated acute ischemic infarction in the ‎brainstem. The abnormal MRI findings concerning the ischemic lesions were interpreted on standard axial 5 mm and thin-section coronal 3mm DWI. RESULTS: The mean age of the studied group was 69.2 ± 4.3 for male and 72.3 ± 2.5 years. The standard axial DWI can diagnose 20%, 6.7% and 6.7% of the infarctions in midbrain, pons an

The matter of handwritten text recognition is as yet a major challenge to mainstream researchers. A few ways deal with this challenge have been endeavored in the most recent years, for the most part concentrating on the English pre-printed or handwritten characters space. Consequently, the need to effort a research concerning to Arabic texts handwritten recognition. The Arabic handwriting presents unique technical difficulties because it is cursive, right to left in writing and the letters convert its shapes and structures when it is putted at initial, middle, isolation or at the end of words. In this study, the Arabic text recognition is developed and designed to recognize image of Arabic text/characters. The proposed model gets a single l

The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati

Abstract

This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

     Temperature predicting is the utilization to forecast the condition of the temperature for an upcoming date for a given area. Temperature predictions are done by gathering quantitative data in regard to the current state of the atmosphere. In this study, a proposed hybrid method to predication the daily maximum and minimum air temperature of Baghdad city which combines standard backpropagation with simulated annealing (SA). Simulated Annealing Algorithm are used for weights optimization for recurrent multi-layer neural network system. Experimental tests had been implemented using the data of maximum and minimum air temperature for month of July of Baghdad city that got from local records of Iraqi Meteorological O

An approach for hiding information has been proposed for securing information using Slanlet transform and the T-codes. Same as the wavelet transform the Slantlet transform is better in compression signal and good time localization signal compression than the conventional transforms like (DCT) discrete cosine transforms. The proposed method provides efficient security, because the original secret image is encrypted before embedding in order to build a robust system that is no attacker can defeat it. Some of the well known fidelity measures like (PSNR and AR) were used to measure the quality of the Steganography image and the image after extracted. The results show that the stego-image is closed related to the cover image, with (PSNR) Peak Si