According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through the conveyor belt motion. An optimal speed controlling mechanism of the conveyor belt is presented by detecting smartly the parts' number and weights using the vision sensor, where the latter will give sufficient visualization about the system. Then image processing will deliver the important data to ANN, which will optimally decide the best conveyor belt speed. This decided speed will achieve the aim of power saving in belt motion. The proposed controlling system will optimally switch the speed of the conveyor belt system to ON, OFF and idle status in order to minimize the consumption of energy in the conveyor belt. As the conveyor belt is fully loaded it moves at its maximum speed. But if the conveyor is partially loaded, the speed will be adjusted accordingly by the ANN. If no loading existed, the conveyor will be stopped. By this way, a very significant energy amount in addition to cost will be saved. The developed conveyor belt system will modernize industrial manufacturing lines, besides reducing energy consumption and cost and increasing the conveyor belts lifetime
In IRAQ, the air conditioners are the principal cause of high electrical demand. In summer, the outer temperature sometimes exceeds 500C which significantly effects on the A/C system performance and power consumed. In the present work, the improvement in mechanical and electrical performance of split A/C system is investigated experimentally and analytically. In this paper, performance and energy saving enhancement of a split-A/C system was experimentally investigated to be efficiently compatible with elevated temperature weathers. This improvement is accomplished via Smart Control System integrate with Proportional-Integral- Differential PID algorithm. The PIC16F877A micro-controller has been programmed with the PID and PWM c
... Show MoreIn this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For
... Show MoreThe speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T
Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer
... Show MoreIn this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe
... Show MoreIn Production and Operations Management the specialists have tried to develop a strategy to counter the risks arising from the activities of the organization and of waste of various types and therefore the risk management in the contemporary framework represents a phenomenon of new quality, and can not be this phenomenon to take practical dimensions, but the development of culture of the organization towards the risks and deal with all aspects and paint ways to address them within an integrated program, and requires new skills and systems provide accurate information capable of coordination between the various parties within the organization.
The research aims to develop a blu
... Show MoreIn this research project, a tip-tilting angle of a photovoltaic solar cell was developed to increase generated electrical power output. An active, accurate, and simple dual-axis tracking system was designed by using an Arduino Uno microprocessor. The system consisted of two sections: software and apparatus (hardware). It was modified by using a group of light-dependent resistor sensors, and two DC servo motors were utilized to rotate the solar panel to a location with maximum sunlight. These components were arranged in a mechanical configuration with the gearbox. The three locations of the solar cell were chosen according to the tilt angle values, at zero angles, which included an optimal 33-degree angle for the Baghdad location and
... Show MoreActive worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.