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Vemulapalli S.,VNR Vignana Jyothi Institute of Engg and Technology | Shashi M.,Andhra University
Advances in Intelligent and Soft Computing | Year: 2012

WWW constitutes huge repository, distributed and dynamically growing hyper medium, supporting access to information and services. As more organizations rely on WWW to conduct business, user behavior analysis becoming difficult in web-based applications. Information about user's interactions with website is stored in server logs and serves as huge electronic survey of website. Web usage mining deals with discovering usage patterns fromserver logs in order to understand and better serve the needs of web users. The raw information contained in log file represents noisy data. Preprocessing includes cleaning, user identification, sessionization, path completion & structurization and is a prerequisite for improving accuracy and efficiency of the subsequent mining process. This paper emphasizes on an effective web log preprocessing system. Experimental results proved that the proposed system reduces the size of log file down to 12% and improves the performance of preprocessing in identifying users, sessions, path completion and structurization. © 2012 Springer-Verlag GmbH Berlin Heidelberg.

Sharada G.,VNR Vignana Jyothi Institute of Engg and Technology | Ramanaiah O.B.V.,Jawaharlal Nehru University
Advances in Intelligent Systems and Computing | Year: 2013

Emotion recognition is an important aspect of Affective Computing. This paper deals with the development of an intelligent agent for automatic recognition of emotion from text based events. The approach chosen is Soft Computing and the architecture used is a Neuro-Fuzzy system. The input (event) string is divided into tokens which are then compared to a standard corpus (i.e.,Wordnet-Affect) of emotional keywords. The computed values of emotional weight and polarity are then processed by a Neuro-Fuzzy Controller, which generates the emotion underlying the event. The system considers Ekman's six basic emotions {Happiness, Despair, Disgust, Fear, Anger, Surprise}. The controller is trained to generate correct output through the backpropagation algorithm. The system is implemented using Java, and, Matlab is used for mathematical analysis. The performance of the system is graded based on the measures of Precision and Accuracy. © 2013 Springer.

Padmasair Y.,VNR Vignana Jyothi Institute of Engg and Technology | SubbaRao K.,Osmania University | Malini V.,Osmania University | Rao C.R.,Central University of Costa Rica
ACE 2010 - 2010 International Conference on Advances in Computer Engineering | Year: 2010

Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures. This study deals with a preliminary investigation to detect epileptic components in the electroencephalogram (EEG) waveform, which results in a reduction of analysis time by the expert neurologist. As an alternative to the Fast Fourier Transform (FFT) spectral analysis approach, an Auto Regressive (AR), a Moving Average (MA) and an Auto Regressive Moving Average (ARMA) model-based spectral estimators can be used to process the EEG signal. An AR signal-processing model for the epileptic EEG is proposed. The AR modelling has been used to analyse physiological signals such as the human EEG. The interpretation of an autoregressive model as a recursive digital filter and its use in spectral estimation are considered. This is used to formulate an analysis model, based on Linear Prediction Coding (LPC). The theory behind the method is explained and the implementation is described. The algorithm is computationally efficient and can be implemented in real-time on a small microcomputer system for on-line analysis. Results produced by this method may be used for further analysis. © 2010 IEEE.

Ramesh Chandra G.,VNR Vignana Jyothi Institute of Engg and Technology | Sathya G.,New York Institute of Technology | Rajan E.G.,Pentagram Research Center Pvt. Ltd. | Coyle M.P.,Avatar MedVision U.S.
Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics | Year: 2014

This paper proposes Cellular Logic Array Processing (CLAP) based 3-D surface detection algorithm. The performance of CLAP based surface detection algorithm (CLAPBSD) is compared with four other algorithms: (i) Boykov and Kolmogorov Based Surface Detection (BKBSD) algorithm, (ii) Push- Relabel (PR) Based Surface Detection (PRBSD) algorithm and (iii) Cheng Wang Ma (CWM) algorithm (iv) Mathematical Morphology Based Surface Detection (MMBSD) in terms of time complexity. © 2014 IEEE.

Krishnasree V.,VNR Vignana Jyothi Institute of Engg and Technology | Balaji N.,Jawaharlal Nehru Technological University Kakinada | Sudhakar Rao P.,Vignan Institute of Technology and Science
WSEAS Transactions on Signal Processing | Year: 2014

One of the main technical goals in the automotive industry is to provide and increase vehicle safety. The traffic accidents are increasing day by day due to a diminished driver's vigilance level and it became a serious problem for the society. By monitoring the fatigue of the driver, the vehicle safety can be improved. Eye detection is an important initial step in Driver Fatigue Detection System. This feature can be used for developing 'Driver fatigue detection system' by monitoring attention or drowsiness of the driver. Robust non-intrusive eye tracking is a crucial step for vision based man-machine interaction technology which is widely accepted in common environments. Eye detection and tracking is an integral part of attentive user interfaces. To detect human eyes, face has to be detected initially. This is done using Open CV face Haar-cascade classifier. After obtaining successful face detection, the location of the eyes is estimated and eye detection is performed using eye haar-cascade classifier. The work aims at development of a driver safety system with visual aid to prevent accidents. The vehicle is equipped with USB web camera interfaced to the system. Here the camera is used for tracking the eyes of driver to detect fatigue. The driver assistance system unit consists of a BEAGLE BOARD with a DM3730 processor in it. The system runs on an embedded operating system called Angstrom. The system architecture deals with the development of device driver for USB web camera and DM3730 processor in standard Linux kernel. Open CV package is installed to interface USB web camera with the navigation system. Open CV package consists of various image processing functions, which are useful for identification of driver fatigue. Open CV is used as a platform to develop a code for eye detection in real time. The code is then implemented on the Beagle board (Ported with Angstrom Operating System) installed with Open CV software.

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