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Fault diagnosis of induction motor is gaining importance in industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. Due to environmental stress and many others reasons different faults occur in induction motor. Many researchers proposed different techniques for fault detection and diagnosis. However, many techniques available presently...
Monitoring driver fatigue, inattention, drowsiness and alertness is very important in order to prevent vehicular accidents. The system detecting and monitoring should be noninvasive type and non-distracting to the driver. The physiological parameters such as skin conductance, oximetry pulse, respiration, SPO2 and BVP can lead to the acceptable solution to the problem. The author is working on the...
The growing usage of mobile camera phones has led to proliferation of many mobile applications. Landmark recognition is one of the mobile applications that are gaining more attention in recent years. The main idea of the application is that a user will use a camera phone to capture the image of a landmark or building and then the system will analyze, identify, and inform the user the name of the captured...
The paper provides a novel approach to emotion recognition from facial expression and voice of subjects. The subjects are asked to manifest their emotional exposure in both facial expression and voice, while uttering a given sentence. Facial features including mouth-opening, eye-opening, eyebrow-constriction, and voice features including, first three formants: F1, F2, and F3, and respective powers...
India is a multi-lingual multi-script country, where eighteen official scripts are accepted and there are over hundred regional languages. In this paper we propose a zone-based hybrid feature extraction algorithm scheme towards the recognition of off-line handwritten numerals of two popular south-Indian scripts. The character centroid is computed and the character/numeral image (50 ?? 50) is further...
In this paper, a three tier strategy is suggested to recognize the hand-printed characters of Devanagari script. In primary and secondary stage classification, the structural properties of the script are exploited to avoid classification error. The results of all the three stages are reported on two classifiers i.e. MLP and SVM and the results achieved with the later are very good. The performance...
Recently a new method for recognition of isolated handwritten Persian digits, based on support vector machines (SVMs), has been introduced. In this research, this method was implemented for the same task with three new modifications, i.e. only one popular shape was considered for digits written in different shapes; sizes of glyphs normalized to digit boundaries; MLP (multi-layer perceptron), SVM/MLP...
We propose a new ultrasonic image analysis system that can be utilized as an effective tool in classifying liver states as normal, hepatitis, or liver cirrhosis. In this system, we first define suitable settings for the ultrasonic device, then remove the inhomogeneous structures from the area of interest in the image, and then, by using the forward sequential search method, look for the useful texture...
All sections of the society need to benefit from the strides in Information Technology, more so the differently enabled. This paper presents a Novel solution for a text read out OCR system adapted for the visually challenged. A paper of text from Malayalam magazines, newspapers, books or journals placed on a flatbed scanner would be recognized and read out as text. Selected text could also be printed...
The increasing complexity of modern distributed systems makes conventional fault tolerance and recovery prohibitively expensive. One of the promising approaches is online failure prediction. However, the process of feature extraction depends on the experienced administrators and their domain knowledge to filtering and compressing error events into a form that is easy for failure prediction. In this...
Classification of electroencephalogram (EEG) is a crucial issue for EEG-based brain computer interface (BCI) system. In this paper, the performances of the Gaussian process classifier (GPC) for three different categories of EEG signals, i.e. steady state visually evoked potential (SSVEP), motor imagery and finger movement EEG data, are investigated. The main purpose of this paper is to explore the...
Radar emitter identification has attracted increasing interests in the last decade. The class-dependent method in to optimize time-frequency kernel of ambiguity function (AF) needs to rank kernel points in the whole AF plane and is sensitive to sampling data length. In this paper, an ambiguity function zero-slice based feature optimization algorithm is proposed for radar emitter recognition. It efficiently...
The paper provides a novel approach to emotion recognition from facial expression and voice of subjects. The subjects are asked to manifest their emotional exposure in both facial expression and voice, while uttering a given sentence. Facial features including mouth-opening, eye-opening, eyebrow-constriction, and voice features including, first three formants: F1, F2, and F3, and respective powers...
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...
Maritime security includes reliable identification of ship entering and leaving a nation's territorial waters. Automated systems that could identify a ship could complement existing electronic signal identification methods. The use of Forward Looking Infrared (FLIR) and Synthetic Aperture Radar (SAR) enables ship image acquisition round-the-clock but their cost and complexity means few installations...
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...
Visual evaluation of long-term EEG recordings is very difficult, time consuming and subjective process. This paper aims to present the research and development of a comprehensive scheme for computer-assisted recognition of behavioral states of sleep in newborns. In clinical practice, the ratio of behavioral states (wakefulness, quiet and active sleep) is used as an important indicator of the brain...
The objective of this study was to evaluate the usefulness of AM-FM features extracted from surface electromyographic (SEMG) signals for the assessment of neuromuscular disorders at different force levels. SEMG signals were recorded from a total of 40 subjects, 20 normal and 20 patients, at 10%, 30%, 50%, 70% and 100% of maximum voluntary contraction (MVC), from the biceps brachii muscle. From the...
In this study we present an integrated system for supporting the diagnosis of endometrial cancer. The system consists of an electronic patient record that incoporates a hysteroscopy imaging CAD system for the early detection of endometrial cancer. The electronic patient record is based on information collected from: appointments, patient info, hysteroscopy reporting and pharmacy. The CAD system is...
In this paper SVM algorithm is applied to classify the scenery video types in compressed domain. Firstly we extract video sequences randomly from scenery video and detect representative frames from the video sequences; secondly we extract features such as color layout, dominant color, edge histogram and face feature; then according to SVM, representative frames are classified as natural scenery, personality,...
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