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The ultimate bond strength between Fiber Reinforced Polymers (FRP) and concrete is one of the most important elements in the performance of the strengthened beam and its failure mode and failure mechanism. In this investigation an Artificial Neural Network (ANN) model has been developed to predict the ultimate bond strength (Pu) between FRP and concrete based on several factors that influence it....
Maintaining the performance of reliable transport protocols, such as TCP, over wireless mesh networks is a challenging problem due to the unique characteristics of wireless mesh networks such as the lossy nature of the communication medium, absence of a base station, similarity in traffic pattern experienced by neighboring mesh nodes, etc. One of the reasons for the poor performance of conventional...
Steam Boilers are important equipment in power plants and the boiler trips may lead to the entire plant shutdown. To maintain performance in normal and safe operation conditions, detecting of the possible boiler trips in critical time is crucial. As a potential solution to these problems, an artificial intelligent monitoring system specialized in boiler high temperature superheater trip has been developed...
This paper presents a Transfer Module for an English-to-Arabic Machine Translation System (MTS) using an English-to-Arabic Bilingual Corpus. We propose an approach to build a transfer module by building a new transfer-based system for machine translation using Artificial Neural Networks (ANN). The idea is to allow the ANN-based transfer module to automatically learn correspondences between source...
Dimensionality reduction is an essential task for many large-scale information processing problems such as classifying document sets, searching over Web data sets, etc. It can be used to improve both the efficiency and the effectiveness of classifiers. In this paper, a comparative study is conducted of five Dimension Reduction Techniques in the context of the Arabic text classification problem using...
Cognitive Radio (CR) can access the spectrum temporarily to solve the problem of the near spectrum crunch. The previous transmissions' events are one of the main motivations for the CR actions and its learning procedures. Therefore, self aware CR devices may cause a considerable interference when they transmit for the first time with no practical knowledge. This paper proposes a solution for cognitive...
In this paper, an automatically skin cancer classification system is developed and the relationship of skin cancer image across different type of neural network are studied with different types of preprocessing.. The collected images are feed into the system, and across different image processing procedure to enhance the image properties. Then the normal skin is removed from the skin affected area...
In this paper, we present an intelligent approach to analysing prostrate ultrasound images in order to diagnose prostate cancer. Algorithms based on fuzzy image processing are applied first to enhance the contrast of the original image, to extract the region of interest and to enhance the edges surrounding that region. Then, we extract features characterising the underlying texture of the regions...
This study presents a performance analysis of a neural observer applied to speed and radial position controls of an induction-type bearingless motor with divided windings. The speed and radial control actions are carried out in conjunction with current control in the windings. The neural flux observer aims at compensating possible parametric variations of the machine caused by agents such as temperature...
A number of image analysis applications are already available to classify the shape of aggregate. These applications were evaluated and compared with our new alternative application called aggregate shape classification system (ASHAC). This newly developed direct measurement methods have the potential to objectively classify two types of aggregate known as well-shaped (fine) aggregate and poor-shaped...
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