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Crack is a common form of pavement distress and it carries significant information on the condition of roads. The detection of cracks is essential to perform pavement maintenance and rehabilitation. Many of the highways agencies, in different countries, are still employing conventional, costly and very time consuming techniques which involve direct human(More)
Stable aqueous monodispersed silver nanoparticles were synthesised by reducing silver nitrate using various sugars such as glucose, fructose, lactose, and sucrose at 55-60 C. A mixture of two stabilising agents, polyvinyl pyrrolidone (PVP) of molecular weight (MW 40, 000) and gelatin plays a decisive part in controlling size and shape of superfine silver(More)
Knocking in SI (Spark Ignition) engines is one of the most addressable problems. If not detected in early stages, it causes a severe damage to an SI engine. Various techniques have been proposed so far, in order to detect early knock symptoms. This paper presents a novel approach to detect knocking using technique of Artificial Intelligence. A four stroke,(More)
Road crack identification is a prerequisite for both road health monitoring and reduction in reconstruction outlay. This paper proposes a Bayesian approach for pavement crack detection. The task is challenging because there is a small difference between a crack and noise besides the cracks have a strong variance in intensity throughout. The devised solution(More)
Detection of corrosion in industrial pipes and tubes is a challenging task. This paper presents an efficient and a low-cost approach for corrosion detection and classification. The proposed approach combines the guided acoustic waves and Radial Basis Function Neural Network (RBF-NN) classifier. Mean, RMS, Variance, Kurtosis and Skewness are used as distinct(More)
Combined cycle power plants are frequently used for power production. Predicting the power plant output based on operational parameters is in major focus nowadays. The paper presents a novel approach using a particle swarm optimization trained feedforward neural network to predict power plant output. It takes ambient temperature, atmospheric pressure,(More)
A ball-bot is an extremely agile mobile robotic platform due to its inherent instability. In order to maneuver at high speeds, a specialized controller is needed. A ball-bot can be modelled as two decoupled, 2-DOF pendulum on a cart systems. These systems comprise a classical and frequently encountered problem in the area of control theory. This paper(More)
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