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Logic gates are an indispensable part of digital circuits, and therefore such devices with fast operating speeds and simple designs are vital for all kinds of electronic applications. This paper proposes simple Y‐shaped designs of all‐optical AND, OR, and NOT logic gates in two dimensions that are operational in both TE and TM modes. These gates are designed using silicon slab waveguides, which makes...
Emotion Recognition from speech has evolved itself as the most significant research area in the field of affective computing. In this paper, two emotional speech datasets, have been analyzed, based on gender distinction (male and female speech). This paper introduces a new approach of speech-emotion recognition based on the use of AdaBoost classification Algorithm. Artificial neural network has been...
Higher Education Program (HEP) is the back bone for progress of every country as it produces the required trained manpower for industry and academia. For industrial development the quality of the manpower is very critical being the direct proportional for the quality of the product. Similarly in academia the trained and well qualified people can only produces the quality manpower. This can be well...
A Delay Tolerant Network (DTN) is characterised as partitioned networks with absence of end to- end connectivity and therefore conventional routing techniques applicable to MANET cannot be applied. DTN have found to be useful in number of application areas where prioritization of messages is essential. We have worked with prioritization of messages considering minimum consumption of network resources...
Path finding in major cities based on specific (or particular) requirements is one of the significant problems that city travellers face as well as a challenging demand or need for the car based navigation systems. Therefore, in this paper, we introduced a multi-parameter (taking more than one parameter into consideration) based path finding modern system which utilizes fuzzy logic to an Ant Colony...
In recent year's artificial neural network has found its application in diagnosing the disease, based upon prediction from previously collected dataset. In this paper, two different artificial neural networks are proposed for disease diagnosis, which uses Scaled Conjugate gradient backpropagation and Levenberg-Marquardt backpropagation algorithm for training the neural networks. The proposed model...
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