National Institute of Technology, Meghalaya

About: National Institute of Technology, Meghalaya is a education organization based out in Shillong, India. It is known for research contribution in the topics: Control theory & Electric power system. The organization has 503 authors who have published 1062 publications receiving 6818 citations. The organization is also known as: NIT Meghalaya & NITM.

Emotion recognition from face dataset using deep neural nets

Abstract: The work presents an approach towards facial emotion recognition using face dataset consisting of four classes of emotions (happy, angry, neutral and sad) with different models of deep neural networks and compares their performance. We take the raw pixels values of all images in CMU face images dataset. The pixels values were represented by higher level concepts by feeding them into Restricted Boltz-mann Machine, Deep Belief Networks and Stacked Autoencoder with Softmax Function. We observe that the later model could learn to recognize emotion with significantly higher accuracy compared to the former two models. Also, its performance improves with an increase in the number of hidden nodes in autoencoders, unlike the other two models.

Improved NCV Gate Realization of Arbitrary Size Toffoli Gates

Abstract: The problem of synthesis and optimization of reversible and quantum circuits have drawn the attention of researchers in recent years. The typical design flow for such circuits first carries out the step of synthesis in terms of reversible gates, and then maps (decomposes) each reversible gate into equivalent set of quantum gates (e.g. from the NCV library). Since its initial proposal in realizing a Toffoli gate using quantum gates, several structural modifications have been proposed in the literature in order to reduce the cost of the generated netlist. The most recently introduced approach produces improved NCV cascade successively by partitioning the control lines of the given Toffoli gate in all possible ways, and replacing intermediate Toffoli gates with optimized equivalent NCV cascades form a catalog. In this approach the complexity of decomposing large Toffoli gates is high. In the present paper an efficient heuristic for partitioning the control lines of a given Toffoli gate is proposed. This heuristic is used for decomposition of the Toffoli gate without using any NCV catalog, after applying a template based optimization step. The cost of resultant circuit is similar to or sometimes better than the one reported by previous approaches.

Investigation on cutting of thin carbon fiber-reinforced polymer composite plate using sandwich electrode-assisted wire electrical-discharge machining:

Abstract: This paper presents the experimental investigation on cutting of thin carbon fiber-reinforced polymer (CFRP) composite plate by wire electrical-discharge machining (WEDM) with the aid of sandwich a...