(SoE) School of Engineering

<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

This paper proposes a reinforcement learning (RL)-based game-theoretic formulation for designing robust controllers for nonlinear systems affected by bounded external disturbances and parametric uncertainties. Based on the theory of Markov games, we consider a differential game in which a 'disturbing' agent tries to make worst possible disturbance while a 'control' agent tries to make best control input. The problem is formulated as finding a min-max solution of a value function. We propose an online procedure for learning optimal value function and for calculating a robust control policy. Proposed game-theoretic paradigm has been tested on the control task of a highly nonlinear two-link robot system. We compare the performance of proposed Markov game controller with a standard RL-based robust controller, and an H∞ theory-based robust game controller. For the robot control task, the proposed controller achieved superior robustness to changes in payload mass and external disturbances, over other control schemes. Results also validate the effectiveness of neural networks in extending the Markov game framework to problems with continuous state-action spaces. © 2006 Elsevier B.V. All rights reserved.

World University root node

Electrical Engineering

Applied Soft Computing Journal

A robust Markov game controller for nonlinear systems

Let G = (V, E) be an undirected weighted graph on |V| = n vertices and |E| = m edges. A t-spanner of the graph G, for any t ≥ 1, is a subgraph (V, ES), ES ⊆ E, such that the distance between any pair of vertices in the subgraph is at most t times the distance between them in the graph G. Computing a t-spanner of minimum size (number of edges) has been a widely studied and well-motivated problem in computer science. In this paper we present the first linear time randomized algorithm that computes a t-spanner of a given weighted graph. Moreover, the size of the t-spanner computed essentially matches the worst case lower bound implied by a 43-year old girth lower bound conjecture made independently by Erdos, Bollobás, and Bondy &amp; Simonovits. Our algorithm uses a novel clustering approach that avoids any distance computation altogether. This feature is somewhat surprising since all the previously existing algorithms employ computation of some sort of local or global distance information, which involves growing either breadth first search trees up to Θ(t)-levels or full shortest path trees on a large fraction of vertices. The truly local approach of our algorithm also leads to equally simple and efficient algorithms for computing spanners in other important computational environments like distributed, parallel, and external memory. © 2006 Wiley Periodicals Inc.

Random Structures and Algorithms

A simple and linear time randomized algorithm for computing sparse spanners in weighted graphs

Civil Engineering

44th Annual Technical Meeting of Society of Engineering Science

A new multiscale approach to failure analysis of composite plates and shells

ECS Transactions

Parasitic effects depending on shape of spacer region on FinFETs

Second Breakdown phenomenon (It2) in drain extended NMOS (DENMOS) which is associated with complex triggering of the parasitic BJT is relatively less understood. We present experiments and models to understand the physics of snapback in DENMOS in nanometer scale technologies. Avalanche injection phenomenon at the drain contact has been analyzed for a 90 nm DENMOS transistor under high current stressing. © 2007 IEEE.

Annual Proceedings - Reliability Physics (Symposium)

An insight into the high current ESD behavior of drain extended NMOS (DENMOS) devices in nanometer scale CMOS technologies

This paper highlights the modeling, simulation and detection of deposited scales in boiler tubes by Pulsed Thermography (PT). A novel data analysis method, based on variations of slopes in Temperature-Time profiles approach has been adopted, to estimate subsurface scale thickness and material loss in the tubes. The slopes are obtained for different pixels in the field of view of the captured image sequence during transient heating of the boiler tube. Relative thickness variations due to material loss and the deposited scales of boiler tube have been estimated from the calculated slopes. Experimental results are presented in support.

Proceedings of SPIE - The International Society for Optical Engineering

Thermal non-destructive evaluation of scaling in boiler tubes

The alias-free nature of non uniform sampling schemes can be used to design wideband digitizers. Existing non uniform digitizer designs have a finite alias-free bandwidth because of time quantization of sampling instants. This paper proposes a new design for a non uniform digitizer in which the sampling instants are no longer time quantized. Hence, there is no upper limit on the alias-free bandwidth and the entire analog bandwidth of the digitizer front end can be used for alias-free sampling of a wideband analog waveform. ©2007 IEEE.

IEEE Region 10 Annual International Conference, Proceedings/TENCON

Non uniform digitizer for alias-free sampling of wideband analog signals

9th United States National Congress on Computational Mechanics

Eigendeformation-based reduced order homogenization

When performing classification of large set of samples, Neural Trees (NTs) are preferably used. To circumvent the problem of poor generalization of Neural Trees, hybrid Neural Trees have been proposed. Recently hybrid SVM based Neural Tree has been shown to be an effective binary classifier. In this paper, we examine the performance of SVM based Neural Trees relative to the nonlinear SVMs. We observe that nonlinear SVMs are more effective, though at higher computational cost. Our conclusions will provide important guidelines in data mining applications on real world datasets. © 2007 IEEE.

Proceedings - International Conference on Information Technology-New Generations, ITNG 2007

Binary classification by SVM based neural Trees and nonlinear SVMs

Levels of fine Particulate Matter (PMfine), SO2 and NOx are interlinked through atmospheric reactions to a large extent. NOx, NH3, SO2, temperature and humidity are the important atmospheric constituents/conditions governing formation of fine particulate sulfates and nitrates. To understand the formation of inorganic secondary particles (nitrates and sulfates) in the atmosphere, a study was undertaken in Kanpur, India. Specifically, the study was designed to measure the atmospheric levels of NH4+, Ca2+, Mg 2+, Na+, K+, NO3-, SO42-, CI-, NH3 (gas), HNO 3 (gas), NO2 and PM10 (PM2.5/PM 10 ratio = 0.74) covering winter and summer seasons and day and night samplings to capture the diurnal variations. Results showed NO3 -, SO42-, NH4+, K + are found to be significantly high in winter season compared to the summer season. In winter, the molar ratio of NH4+, SO42- was found to be greater than 2:1. This higher molar ratio suggests that in addition to (NH4)2SO4, NH4NO3 will be formed because of excess quantity of NH4+, present. In summer, the molar ratio was less than 2:1 indicating deficit of NH4+, to produce NH 4NO3. The nitrogen conversion ratio (NO2 to NO3) was found to be nearly 50% in the study area that suggested quick conversion of NO2 into nitric acid. As an overall conclusion, this study finds that NH3 plays a vital role in the formation of fine inorganic secondary particles particularly so in winter months and there is a need to identify and assess sources of ammonia emissions in India. © 2007 Springer Science+Business Media B.V.