Khairul Azha A Aziz

A simple method for the determination of the inhibition efficiency of surfactants

Abstract The dissolution of aluminium and zinc in hydrochloric acid solutions has been studied by the thermometric method of Mylius and the variation of the reaction number (R.N.) of both metals with the concentration of the acid has been established, The effect of a large number of additives on the R.N. of aluminium in 2 N HCl and zinc in 3 N HCl has been examined. Additives lowering the R.N. act as inhibitors, while those raising it are corrosion accelerators. Differentiation can be made between weakly and strongly adsorbed inhibitors. R.N.—log [inhibitors] curves are invariably sigmoid in shape. The points of inflexion of these curves depend upon the type of the inhibitor used and R.N. varies linearly and logarithmically with the concentration of the inhibitor before and after the inflexion points. The experimental results have been fitted into known adsorption isotherms. The inhibition efficiency of a number of additives, as determined by the thermometric method,was compared with that obtained by weight loss measurements and agreement was satisfactory. The results of a limited number of experiments on corrosion accelerators are described. Increasedcorrosion is related to an easier reduction reaction than hydrogen evolution. Additives leading to the formation of a metallic deposit of low hydrogen overpotential are harmful. The accelerated corrosion can be inhibited by the addition of the proper surfactant.

Face Detection Using Radial Basis Function Neural Networks with Variance Spread Value

This paper present a face detection system using Radial Basis Function Neural Networks With Variance Spread Value. Face detection is the first step in face recognition system. The purpose is to localize and extract the face region from the background that will be fed into the face recognition system for identification. General preprocessing approach was used for normalizing the image and a Radial Basis Function (RBF) Neural Network was used to distinguish between face and non-face images. RBF Neural Networks offer several advantages compared to other neural network architecture such as they can be trained using fast two stages training algorithm and the network possesses the property of best approximation. The output of the network can be optimized by setting suitable values of the center and spread of the RBF. In this paper, variance spread value will be used for every cluster where the value of spread will be calculated using algorithm. The performance of the RBFNN face detection system will be based on the detection rate, False Acceptance Rate (FAR) and the False Rejection Rate (FRR) criteria.

Hybrid vibration energy harvester based on piezoelectric and electromagnetic transduction mechanism

Vibration energy harvester converts kinetic energy from ambient vibration into electrical energy. Many energy harvesters in the literature use single element transducer, either piezoelectric, electromagnetic or electrostatic for above purpose. In this paper, a hybrid based energy harvester that integrates with both, piezoelectric and electromagnetic transducers is developed and examined. The energy harvester uses four pole magnets arranged onto a piezoelectric cantilever beam free end, to produce stronger magnetic field over a stationary coil. When the harvester is excited by an external vibration, both piezoelectric and electromagnetic generates electrical energy or power. Experimental results shows that piezoelectric capable to generate optimum power of 2.3mW in a 60Ω resistive load, while electromagnetic generates 3.5mW power in a 40Ω resistive load, when vibrated at its resonant frequency 15Hz, and at 1g (1g=9.8ms-2) acceleration. By efficiently integrating both piezoelectric and electromagnetic transducers, more power could be generated as compared to a single transducer over its size.

A pixel to pixel correspondence and region of interest in stereo vision application

This paper presents an analysis of stereo images for an application of stereo vision application. The correspondence process is to determine the difference of intensities of pixel between stereo images while the region of interest ROI works as a reference area to the stereo vision application. This region is a reference view of the stereo camera and stereo vision baseline is based on horizontal configuration. The block matching technique is briefly described with the performance of its output. The disparity mapping is generated by the algorithm with the reference to the left image coordinate. The algorithm uses Sum of Absolute Differences (SAD) which is developed using Matlab software. The rectification and block matching processes are also briefly described in this paper.

Visualization of image distortion on camera calibration for stereo vision application

This paper presents a visualization of image distortion on camera calibration for stereo vision application. The 3D image plane in a group of target or image during the process of stereo pair calibration is also discussed. The extrinsic parameters of camera calibration can be viewed in 3D image or scene which contains the rotation and translation of vector. The error re-projection of a single image could determine the less error of distortion during the extraction of chessboard corner each image taken. The distortion model also generates an error coordinate system in pixel value. The 3D image will viewed the result and output of extrinsic parameters during the calibration process.

A New Object Recognition Approach Using Combination of Texture, Color and Shape Features

This paper reports a new approach for recognizing objects by using combination of texture, color and shape features. Texture features were generated by applying statistical calculation on the image histogram. Color features were computed by using mean, standard deviation, skewness and kurtosis. Shape features were generated using combination of Shen features and basic shapes such as eccentricity and dispersion. The total features were used much less compared to approaches that involve orthogonal moments such as Krawtchouk moments, Zernike moments, or Tchebichef moments. Testing was done by using a dataset that contains 53 kinds of objects. All objects contained in the dataset were various things that can be found in supermarkets or produced by manufacturing. The result shows that the system gave 98.11% of accuracy rate.

Product Identification Using Image Processing and Radial Basis Function Neural Networks

This paper presents a product identification using image processing and radial basis function neural networks. The system identified a specific product based on the shape of the product. An image processing had been applied to the acquired image and the product was recognized using the Radial Basis Function Neural Network (RBFNN). The RBF Neural Networks offer several advantages compared to other neural network architecture such as they can be trained using a fast two-stage training algorithm and the network possesses the property of best approximation. The output of the network can be optimized by setting suitable values of the center and the spread of RBF. In this paper, fixed spread value was used for every cluster. The system can detect all the four products with 100% successful rate using ±0.2 tolerance.

A pixel matching process and multiple ROI for stereo images in stereo vision application

This paper presents an analysis of stereo images for an application of stereo vision application. The matching process is to determine the difference of intensities of pixel between stereo images while the region of interest ROI works as a reference area to the stereo vision application. This region is a reference view of the stereo camera and stereo vision baseline is based on horizontal configuration. The block matching technique is briefly described with the performance of its output. The disparity mapping is generated by the algorithm with the reference to the left image coordinate. The algorithm uses Sum of Absolute Differences (SAD) which is developed using Matlab software. The rectification and block matching processes are also briefly described in this paper.