College of Engineering, Pune

About: College of Engineering, Pune is a based out in . It is known for research contribution in the topics: Sliding mode control & Control theory. The organization has 4264 authors who have published 3492 publications receiving 19371 citations. The organization is also known as: COEP.

Learning style recognition using Artificial Neural Network for adaptive user interface in e-learning

Abstract: Traditionally e-learning systems are emphasized on the online content generation and most of them fail in considering the requirements and learning styles of end user, while representing it. Therefore, appears the need for adaptation to the user's learning behavior. Adaptive e-learning refers to an educational system that understands the learning content and the user interface according to pedagogical aspects. End users have unique ways of learning which may directly and indirectly affect on the learning process and its outcome. In order to implement effective and efficient e-learning, the system should be capable not only in adapting the content of course to the individual characteristics of students but also concentrate on the adaptive user interface according to students' requirements. In this paper, at initial stage we are presenting an approach to recognize the learning styles of individual student according to the actions or navigations that he or she has performed on an e-learning application. This recognition technique is based on Machine Learning algorithm called Artificial Neural Networks and Web Usage Mining.

Nonlinear Control for Dual Objective Active Suspension Systems

Abstract: In this paper, an active suspension system employing a new nonlinear control law is proposed to address the problem of achieving the dual objective of providing ride comfort and trying to keep the suspension deflection within the constraint of rattle space. The control is a nonlinear function of the magnitude of the suspension deflection and an estimate of the effect of the road disturbance. The control scheme is analyzed and assessed for the large classes of road profiles through simulation and by experimentation on a laboratory setup. The performance of the proposed scheme is compared with a passive suspension system.

Negative Differential Resistance in Boron Nitride Graphene Heterostructures: Physical Mechanisms and Size Scaling Analysis

Abstract: Hexagonal boron nitride (hBN) is drawing increasing attention as an insulator and substrate material to develop next generation graphene-based electronic devices. In this paper, we investigate the quantum transport in heterostructures consisting of a few atomic layers thick hBN film sandwiched between graphene nanoribbon electrodes. We show a gate-controllable vertical transistor exhibiting strong negative differential resistance (NDR) effect with multiple resonant peaks, which stay pronounced for various device dimensions. We find two distinct mechanisms that are responsible for NDR, depending on the gate and applied biases, in the same device. The origin of first mechanism is a Fabry-Perot like interference and that of the second mechanism is an in-plane wave vector matching when the Dirac points of the electrodes align. The hBN layers can induce an asymmetry in the current-voltage characteristics which can be further modulated by an applied bias. We find that the electron-phonon scattering suppresses the first mechanism whereas the second mechanism remains relatively unaffected. We also show that the NDR features are tunable by varying device dimensions. The NDR feature with multiple resonant peaks, combined with ultrafast tunneling speed provides prospect for the graphene-hBN-graphene heterostructure in the high-performance electronics.