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Many of the electrical systems throughout the world are experiencing problems with aging insulation. When an insulation system fails, the results are usually catastrophic. Insulation failure can cause sustained interruption which can cause substantial financial loses due to lost production and damage to expensive equipment. These losses can amount to thousands of ringgit (RM) per hour. With the ability...
The study of the behavior of ion-channels can provide significant information to detect metal ions and small organic molecules in solution. Discrimination of different analytes can be performed by extracting appropriate features from the ion-channel signals and using them for classification. In this paper, we consider features extracted from the Fourier, Wavelet and Walsh-Hadamard domain representations...
Multiple-extremum issue including the well-known ??singularity?? problem is one of the major defects in kernel-based object tracking. This paper studies this important problem and presents a novel approach called section-based tracking (SBT) that is based on the section information provided by the division of the object's weight image. This approach serves to eliminate fake extremal points and make...
The classification of Raman spectra is useful in identification and diagnosis applications. We have obtained Raman spectra from bacterial samples using three different species of bacteria. Before any form of classification can be carried out on the Raman spectra it is important that some form of normalization is used. This is due to the nature of the readings obtained by the acquisition equipment...
We present applications of recently developed algorithms for data-driven nonlinear systems identification to the study of cardiovascular and respiratory control mechanisms on an integrated systems level, utilizing experimental data obtained during resting conditions. Specifically, we consider cerebrovascular regulation during normal conditions in a two-input context, as well as respiratory control...
Recent advances in the power and resolution capabilities of MR scanners have extended the reach of magnetic resonance spectroscopy as a powerful non-invasive diagnostic tool. Coupled with MRI techniques it can provide accurate identification and quantification of biologically important compounds in soft tissue. In practice sensor calibration issues, magnetic field homogeneity effects and measurement...
Snakes, or active contours, are one of the major paradigms in image segmentation and they are extensively applied for the processing of the biomedical images. With the vector field convolution (VFC) as external force, they have a larger capture range and the ability to progress into concave boundaries. However, when we have to deal with highly non-convex shapes, the VFC field forms an area where the...
In some machine learning problems, the dataset has multiple views which may be obtained using different sensors or applying different sampling techniques. These views may have sufficient or partial information about the target concept. In this paper, a method that we called parallel interacting multiview learning (PIML) is proposed in which the views interact during the training process using the...
We construct Kernel Co-occurrence Matrices (KCMs) to represent the target model and the target candidates. Then those matrices are employed as the tracking cues in mean shift framework. Some improvements are presented in the implementation of the algorithm. First, the angle relation between pixel-pairs is redefined to depict the asymmetric characteristic of the object. Second, the KCMs of the target...
With the introduction of multi-core processors, a balance between access contention of the cache and availability of cached data for multiple cores has to be addressed. Processor manufacturers are finding this compromise through a combination of private and shared cache structures, where the last level cache (LLC) may not be shared across all processing cores. This poses an interesting opportunity...
In most parts of the world, the quality of the electrical power has become a major concern for many electricity users especially the industrial customers. To the power utility, all power quality disturbances must be detected, classified and diagnosed accurately so that proper mitigation measures can be implemented. This paper presents the application of the S-transform and support vector machine (SVM)...
This paper proposes a new probabilistic method for maximum temperature forecasting in short-term electrical load forecasting. The proposed method makes use of Gaussian process (GP)of the kernel machine to evaluate the predicted temperature. In recent years, electric power markets become more deregulated and competitive. The power system players are concerned with maximizing a profit while minimizing...
This paper investigates a ARM and FPGA-based hybrid-processors real-time embedded Linux platform. This platform is designed as a general purpose embedded system that can be fitted into a number of applications such as digital controller, embedded web server or base station in wireless sensor networks. However, its hybrid-processors feature makes it a perfect experimental platform for scientific research...
This paper presents a hardware architecture for calculating the city-block and chessboard distance transform on binary images. It is based on applying multiple morphological erosions and adding the result, enabling both processing pixels in raster scan order and a deterministic execution time. Which distance metric to be calculated is determined by the shape of the structuring element, i.e. diamonds...
A configurable SoC platform based on LEON3 microprocessor and Linux operation system (SnapGear) is presented in this paper. A novel method is proposed, which adds a new peripheral (SPI) to the SoC and designs a device driver according to Linux device model. In this way, customers can add hardware to LEON SoC and enhance the system functions by using device driver easily, which are proved by the testing...
This paper presents a vector median filter that includes a new mechanism for the detection of impulses in color images prior to further processing operations. The proposed filter has been tested for images corrupted by two sided fixed impulse noise model. If the central vector pixel in a kernel is found to be corrupted, it is replaced by the vector median of the kernel, else it is kept unchanged....
We describe the implementation and evaluation of a network simulator 2 (NS-2) module for the datagram congestion control protocol, or DCCP. Our module, based on an updated standard described in RFC 4340, attempts to model the behavior and performance of the two currently defined congestion control identifiers CCID2 and CCID3. The behavior, throughput, and fairness of DCCP in comparison with TCP were...
Takagi-Sugeno models are an important class of fuzzy rule based oriented models, generally used for prediction and control. Fuzzy clustering is one of effective methods for identification. In this method, we propose to use a fuzzy clustering method (Kernel based fuzzy c-means method) for automatically constructing a multi-input fuzzy model to identify the structure of a fuzzy model. To clarify the...
In this paper we introduce a statistical method to build two-dimensional gas distribution maps (Kernel DM+V/W algorithm). In addition to gas sensor measurements, the proposed method also takes into account wind information by modeling the information content of the gas sensor measurements as a bivariate Gaussian kernel whose shape depends on the measured wind vector. We evaluate the method based on...
We propose a method to edit RGBNs (images with a color and a normal channel). High resolution RGBNs are easy to obtain using photometric stereo. Free editing will result in normals which do not correspond to any realizable surface. Our normal operators guarantee the integrability of the results. Our method can filter normals with any linear kernel allowing high-pass and edge-enhancement filters. We...
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