National Institute of Technology Calicut

About: National Institute of Technology Calicut is a education organization based out in Kozhikode, Kerala, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 3627 authors who have published 4638 publications receiving 50830 citations. The organization is also known as: Calicut Regional Engineering College & NIT Calicut.

Intuitionistic Fuzzy Multisets And Its Application in Medical Diagnosis

Abstract: In this paper a new concept named Intuitionistic Fuzzy Multiset is introduced. The basic operations on Intuitionistic Fuzzy Multisets such as union, intersection, addition, multiplication etc. are discussed. An application of Intuitionistic Fuzzy Multiset in Medical diagnosis problem using a distance function is discussed in detail. Keywords—Intuitionistic Fuzzy set, Multiset, Intuitionistic Fuzzy Multiset

Classification of eeg signals in normal and depression conditions by ann using rwe and signal entropy

Abstract: EEG is useful for the analysis of the functional activity of the brain and a detailed assessment of this non-stationary waveform can provide crucial parameters indicative of the mental state of patients. The complex nature of EEG signals calls for automated analysis using various signal processing methods. This paper attempts to classify the EEG signals of normal and depression patients using well-established signal processing techniques involving relative wavelet energy (RWE) and artificial feedForward neural network. High frequency noise present in the recorded signal is removed using total variation filtering (TVF). Classification of the frequency bands of EEG signals into appropriate detail levels and approximation level is carried out using an eight-level multiresolution decomposition method of discrete wavelet transform (DWT). Parseval's theorem is used for calculating the energy at different resolution levels. RWE analysis gives information about the signal energy distribution at different decomposition levels. Both RWE and feedforward Network are used to classify the signals from normal controls and depression patients. The performance of the artificial neural network was evaluated using the classification accuracy and its value of 98.11% indicates a great potential for classifying normal and depression signals.

Investigation of mechanical, thermal and water absorption properties of flax fibre reinforced epoxy composite with nano TiO2 addition

Abstract: The present study aims at exploring the influence of nano TiO2 in enhancing the mechanical, thermal and water absorption properties of the flax fibre reinforced epoxy composites. The composites were prepared using the compression moulding technique. Epoxy was modified using nano titanium dioxide (50 nm size) at a loading rate (percentage by weight of the composite) of 0%, 0.5%, 0.7% and 0.9% by mechanical stirring and sonication process. The morphological characterisation was done by Scanning electron microscopy and the structural properties by Fourier transform infrared spectroscopy. The results indicate a significant improvement in strength of the composite system with the addition of TiO2. The optimum weight percentage for maximum performance was obtained as 0.7. The increase in tensile, flexural, impact and interlaminar shear strength values were observed as 10.95%, 20.05%, 10.45% and 18.80% respectively. Water diffusion coefficient was reduced by 31.66% by the addition of nano particles.