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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....
In this paper, an efficient scheme to detect the unprecedented changes in system reliability and find the failed component state by classifying the faults is proposed using kalman filter and hybrid neuro-fuzzy computing techniques. A fault is detected whenever the moving average of the Kalman filter residual exceeds a threshold value. The fault classification has been made effective by implementing...
Improving the diversity of Neural Network Ensembles (NNE) plays an important role in creating robust classification systems in many fields. Several methods have been proposed in the literature to create such diversity using different sets of classifiers or using different portions of training/feature sets. Neural networks are often used as base classifiers in multiple classifier systems as they adapt...
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...
This work focuses on developing cool store's thermal mapping system based on the neuro Wireless Sensor Network (nWSN). The network intelligence is taken care of by the sensor network embedded neural net. The target application of the architecture development is for cool stores with emphasis on meat storage. The meat quality is a significant characteristic within the cold chain management. Temperature...
Cognition is a fundamental feature of natural intelligence, which a modern technology has not yet been able to reproduce in full capacity. Sensor networks provide a new technological support for a substantial increase in an amount and quality of information that might be collected and communicated in complex adaptive systems. Their application may significantly raise the degree of intelligence in...
This paper addresses an interdisciplinary solution for one of the problems associated with computerized educational disciplines. Addressed problem basically concerned with realistic computer-based educational simulations (e-Sims). More specifically, it searches for optimal software learning package(s) applied for teaching of specified curriculum(s) in classroom(s). Herein, quantitative evaluation...
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...
We propose and evaluate a framework for detection of plant leaf/stem diseases. Studies show that relying on pure naked-eye observation of experts to detect such diseases can be prohibitively expensive, especially in developing countries. Providing fast, automatic, cheap and accurate image-processing-based solutions for that task can be of great realistic significance. The proposed framework is image-processing-based...
In this paper, the application of an Artificial Neural Network (ANN) for remedial action of a power system is presented. The aims of this study are to find the significant control action that alleviates a bus voltage violation of a power system and to demonstrate the ability of a neural network in terms of evaluating the generation re-dispatch and load shedding amounts. The remedial action is based...
Searching for the next hop node in mobile sparse wireless sensor networks for data exchange is a challenging task. This involves frequently sending radio beacons that drain battery power and reduces the life of the sensor node. This work proposes a novel energy efficient approach of adaptively sampling the network connectivity. The adaptive sampling starts with random sampling of the network to collect...
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...
The paper presents an upgrading process of rubber tree seed clones identification model using image processing techniques. Sample of rubber tree seeds are captured using digital camera where the RGB color image are processed involving segmentation algorithm which includes thresholding and morphological technique. Texture patterns from seed clones images are then analysed through wavelet's Daubechies...
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...
Satellite remote sensing is an important tool in the detection and short range forecasting (nowcasting) of fog events. Fog over land develops primarily during the late-night and pre-dawn hours, infrared remote sensing is indispensable in observing fog formation at night, while visible imagery helps to monitor the extent and density of fog after sunrise. Satellite remote sensing is widely used in the...
This paper deals with the Fault Detection and Diagnosis of steam boiler using developed artificial Neural networks model. Water low level trip of steam boiler is artificially monitored and analyzed in this study, using two different interpretation algorithms. The Broyden-Fletcher-Goldfarb-Shanno quasi-Newton and Levenberg-Marquart are adopted as training algorithms of the developed neural network...
Surface Electromyography (sEMG) activity of the biceps muscle was recorded from nine subjects. Data were recorded while subjects performed dynamic contraction until fatigue. The signals were initially segmented into two parts (Non-Fatigue and Transition-to-Fatigue) to enable the evolutionary process. A novel feature was evolved by selecting then using a combination of the eleven sEMG muscle fatigue...
Artificial Neural Networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This paper presents the development of a simple ANN topology for load forecasting model with much improved accuracy for the Regional Power Control Centre of Saudi Electricity Company. The proposed system is based on optimising the initial random...
This paper presents a novel ANN based technique for improving the performance of distance relays against open circuit faults in transmission networks. The results obtained show that a distance relay with the proposed scheme will not only be able to detect the open conductor condition in HVTL but also to locate the place of this fault regardless the value of the pre-fault current loading. Detailed...
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