In medical image processing, segmentation is an important and challenging task. It is classically used to identify object contours and extract the object from the image. Tumor Classification is an significant in medical image analysis since it provides information related to anatomical structures as well as possible anomalous tissues necessary to treatment planning and patient follow-up. In thi...

Monitoring system for induction motor is widely developed to detect the incipient fault. Such system is desirable to detect the fault at the running condition to avoid the motor stop running suddenly. In this paper, a new method for detection system is proposed that emphasizes the fault occurrences as temporary short circuit in induction motor winding. The investigation of fault detection is fo...

The ability to accurately forecast data is highly desirable in a wide variety of fields such as sales, stocks, sports performance, and natural phenomena. Presented here is a study of several time series forecasting methods applied to retail sales data, comprising weekly sales figures from various Walmart department stores across the United States over a period of approximately 2 and a half year...

Storytelling is a distinct speaking style which embraces various expressive subtleties aimed to draw the attention of the children. Studies have shown that Text-to-speech (TTS) systems have the tendency of not conveying the right emotion expressivity in their speech outputs. The objective of this work is to develop prosody models to capture the story semantics present in the Hindi children stor...

Magnetic Resonance Images (MRI) are widely used in the diagnosis of Brain tumor. In this study we have developed a new approach for automatic classification of the normal and abnormal non-enhanced MRI images. The proposed method consists of four stages namely Preprocessing, feature extraction, feature reduction and classification. In the first stage anisotropic filter is applied for noise reduc...

a r t i c l e i n f o This paper describes a novel approach to build a piecewise (non)linear surface that separates individuals from two classes with an a priori classification accuracy. In particular, total classification with a good generalization level can be obtained, provided no individual belongs to both classes. The method is iterative: at each iteration a new piece of the surface is fou...

In recent years, an explosion in research on pattern recognition systems using neural network methods has been observed. Face Recognition (FR) is a specialized pattern recognition task for several applications such as security: access to limited areas, banking: identity confirmation and identification of wanted people at airports. Biometric techniques deals with identifying individual with the ...

In this paper, solution of generalized matrix Riccati differential equation (GMRDE) for indefinite stochastic linear quadratic singular system is obtained using neural networks. The goal is to provide optimal control with reduced calculus effort by comparing the solutions of GMRDE obtained from well known traditional Runge Kutta (RK) method and nontraditional neural network method. To obtain th...

Mobile robot’s navigation and obstacle avoidance in an unknown and static environment is analyzed in this paper. From the guidance of position sensors, artificial neural network (ANN) based controllers settle the desired trajectory between current and a target point. Evolutionary algorithms were used to choose the best controller. This approach, known as Evolutionary Robotics (ER), commonly res...