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Measurement of a physical parameter can adversely be affected by several factors like manufacturing process variations, environmental conditions etc. The measured output may non-linearly vary with many of these factors and may cause error in the parameter being measured. A precise modeling of the input-output relationship of measurement systems is indeed a necessity in order to have an accurate measurement...
Dermatological diseases are the most prevalent diseases worldwide. Despite being common, its diagnosis is extremely difficult and requires extensive experience in the domain. In this research paper, we provide an approach to detect various kinds of these diseases. We use a dual stage approach which effectively combines Computer Vision and Machine Learning on clinically evaluated histopathological...
With the increasing usage of mobile devices to ubiquitously access heterogeneous applications in wireless Internet, the measurement, analysis and modeling of Internet traffic has become a key research area. Solving performance related issues of networks and ensuring better Quality of Service (QoS) for end-users calls for simple, tractable and realistic traffic models. The model should not only be...
Electricity market demands to the power industry in de-regulated form in this paper. The proposed load forecasting using ANN shows the effective risk management plans. This power market is to maintain their effective cost in terms of energy generation, energy purchase and optimization of the switching losses. This creates the need of load forecasting. So in this paper the load forecasting using ANN...
Chen, Cybenko, Funahashi, Babri, Gorban, Barron and others studied function approximation capabilities by feed forward neural networks. Ramakrishnan and his collaborators introduced the left sigmoidal and right sigmoidal signals to prove some function approximation theorems in continuous functions. In this paper, the right sigmoidal signal is used to establish function approximation theorems using...
In this paper, we propose a pedestrian analysis solution helpful for adaptive content delivery and interest measurement for outdoor advertisement displays. The proposed system has built-in camera on the top panel of such displays which capture the real time viewers' frames. The captured frames have been analyzed for detection of faces using Viola-Jones algorithm. The detected faces have been processed...
Phonotactic approach, phone recognition to be followed by language modeling, is one of the most popular approaches to language identification (LID). In this work, we explore how language identification accuracy of a phone decoder can be enhanced by varying acoustic resolution of the phone decoder, and subsequently how multiresolution versions of the same decoder can be integrated to improve the LID...
In this paper, a particle swarm optimization (PSO) based camera calibration approach is presented to determine the external and internal calibration parameters from the knowledge of a given set of points in object space. First, the image formation model for a pinhole camera is formulated in terms of a feed-forward neural network (NN) and then this neural network is trained using particle swarm optimization...
In this paper, a stereo framework for a robust real time localization of objects using networkpsilas camera pairs is presented. The stereo system contains a combination of static and pan-tilt-zoom (PTZ) cameras instead of traditional dual head mounted cameras. The proposed novelty consists in applying stereo vision to heterogeneous cameras belonging to a video-surveillance network. First, a look-up-table...
Landmines are significant barrier to financial, economic & social development in various parts of the world. The demand of dependable, trustworthy, intelligent diagnostic systems in the field of landmines detection has been increasing rapidly. Metal detectors used in mine decontamination, cannot differentiate a mine from metallic debris where the soil contains large quantities of metal scrap &...
The English language as spoken by Malaysians varies from place to place and differs from one ethnic community and its sub-group to another. Hence, it is necessary to develop an exclusive speech to text translation system for understanding the English pronunciation as spoken by Malaysians. Speech translation is a process of both speech recognition and equivalent phonemic to word translation. Speech...
Here we have presented an alternate ANN structure called functional link ANN (FLANN) for image denoising. In contrast to a feed forward ANN structure i.e. a multilayer perceptron (MLP), the FLANN is basically a single layer structure in which non-linearity is introduced by enhancing the input pattern with nonlinear function expansion. In this work three different expansions is applied. With the proper...
The prediction of biological activity of a chemical compound from its structural features, representing its physico-chemical properties, plays an important role in drug discovery, design and development. Since the biological data is highly non-linear, the machine-learning techniques have been widely used for modeling it. In the present work, the clustering, genetic algorithm (GA) and artificial neural...
Prognostics and health management enables in-situ assessment of a productpsilas performance degradation and deviation from an expected normal operating condition. A unique hybrid prognostics and health management methodology combining both data-driven and physics-of-failure models is proposed for fault diagnosis and life prediction. The shortcomings of using data-driven and physics-of-failure methodologies...
Multifunctional arm prostheses have been developed since last several decades. One of the major problems that cause the loss of interest in current prostheses is the inadequate control interface between the patient and the prosthesis. The purpose of this research is to investigate the effectiveness of applying the kinematic data of the shoulder and elbow joint to control the arm prosthesis. In this...
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