(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

Total 360 samples (of 8 h each) of PM2.5 were collected from six sampling sites for summer and winter seasons in Kanpur city, India. The collected PM2.5 mass was subjected to chemical speciation for: (1) ionic species (NH+4, SO2-4, NO -3, and Cl-), (2) carbon contents (EC and OC), and (3) elemental contents (Ca, Mg, Na, K, Al, Si, Fe, Ti, Mn, V, Cr, Ni, Zn, Cd, Pb, Cu, As, and Se). Primary and secondary components of PM2.5 were assessed from speciation results. The influence of marine source to PM 2.5 was negligible, whereas the contribution of crustal dust was significant (10% in summer and 7% in winter). A mass reconstruction approach for PM2.5 could distinctly establish primary and secondary components of measured PM2.5 as: (1) Primary component (27% in summer and 24% in winter): crustal, elemental carbon, and organic mass, (2) Secondary component (45% in summer and 50% in winter): inorganic and organic mass, and (3) others: unidentified mass (27% in summer and 26% in winter). The secondary inorganic component was about 34% in summer (NH+4: 9%; SO 2-4: 16%; NO-3: 9%) and 32% in winter (NH+4: 8%; SO2+4: 13%; NO-3: 11%). The secondary organic component was 12% in summer and 18% in winter. In conclusion, secondary aerosol formation (inorganic and organic) accounted for significant mass of PM2.5 (about 50%) and any particulate control strategy should also include control of primary precursor gases. © 2010 American Association for Aerosol Research.

Civil Engineering

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Fulltext

Aerosol Science and Technology

Reconstructing primary and secondary components of PM2.5 composition for an Urban Atmosphere

Two-player zero-sum Markov game framework offers an effective platform for designing robust controllers. In the Markov game-based learning, theoretical convergence of the learning process with the function approximator cannot be guaranteed. However, fusing Q-learning with decision tree (DT) function approximator has shown good learning performance and more reliable convergence. It scales better to larger input spaces with lower memory requirements, and can solve problems that are infeasible using table lookup. This motivates us to introduce DT function approximator in Markov game reinforcement learning (RL) framework. This approach works, though it deals with only discrete actions. In realistic applications, it is imperative to deal with continuous state-action spaces. In this paper, we propose Markov game framework for continuous state-action space systems using fuzzy DT as a function approximator. Simulation experiments on a two-link robot manipulator bring out the importance of the proposed structure in terms of better robust performance and computational efficiency. Copyright © 2010 Inderscience Enterprises Ltd.

Electrical Engineering

International Journal of Automation and Control

A fuzzy decision tree-based robust Markov game controller for robot manipulators

Thin films of Zn1-xCdxS (0.1 ≤ x ≤ 0.5) were prepared by using pulsed laser ablation technique on corning glass substrates. Phase transition from cubic to hexagonal in Zn1-xCdxS films is determined by X-ray diffraction analysis. We observed a lowering in the phase transition temperature with increase in the cadmium concentration. Transmission electron microscopy suggests the crystalline nature of thin films with average particle size of 15 nm. The grown Zn1-xCdxS samples show the high peak intensity ratio of the near band edge emission to the defect center luminescence even at room temperature, which indicates the small concentration of complex defects in the samples. Photoluminescence measurement show stoichiometric dependence of the energy band gap and is found to have quadratic dependence on x.

Journal of Nanoparticle Research

Photoluminescence measurements in the phase transition region of Zn 1-xCdxS films

"Strong Snapback" in DeNMOS transistors leads to weak ESD performance which is often represented by low It2 and strong die to die dependence. We report here the first experimental evidence that this can be controlled with introduction of source-resistance Rs. A new microscopic model has been analyzed to understand the physics of strong snapback and explain the experimental observations. Impact of current crowding phenomenon and role of adding a resistor across the source and ground has been broadly addressed in this paper. Also the current crowding phenomenon has been macroscopically modeled and a circuit model has been established. © 2010 IEEE.

IEEE International Reliability Physics Symposium Proceedings

Robust high current ESD performance of nano-meter scale DeNMOS by source ballasting

In this paper we study the important problems of message routing, sorting, and selection in a radio network. A radio network consists of stations where each station is a hand-held device. We consider a single-hop radio network. In a single-hop network it is assumed that each station is within the transmission range of every other station. Let RN(p, k) stand for a single-hop network that has p stations and k communication channels. The problems of sorting and selection have been studied on RN(p, k). For these problems it is assumed that there are n/p elements to start with at each station. At the end of sorting, the least n/p elements should be in the first station, the next smallest n/p elements should be in the second station, and so on. The best known prior algorithm for sorting takes 4n/k +o (n/k) broadcast rounds on a RN(p, k). In this paper we present a randomized algorithm that takes only 3n k + o (n/k) broadcast rounds with high probability. For the selection problem, it is known that the maximum or minimum element can be found in O(log n) rounds on a RN(n, 1), provided broadcast conflicts can be resolved in O(1) time. The problem of general selection has not been addressed. In this paper we present a randomized selection algorithm that takes O (p k) rounds on a RN(p, k) with high probability. An important message routing problem that is considered in the literature is one where there are n/p packets originating from each station and there are n/p packets destined for each station. The best known routing. © 2010 IEEE.

Computer Science and Engineering

Proceedings of the International Conference on Parallel Processing

An efficient randomized routing protocol for single-hop radio networks

The paper presents a novel framework for learning the hash functions for indexing through Multiple Kernel Learning. The Distance Based Hashing function is applied which does the object projection to hash space by preserving inter object distances. In recent works, the kernel matrix has been proved to be more accurate representation of similarity in various recognition problems. Our framework learns the optimal kernel for hashing by parametrized linear combination of base kernels. A novel application of Genetic Algorithm for the optimization of kernel combination parameters is presented. We also define new texture based feature representation for images. Our proposed framework can also be applied for optimal combination of multiple sources for indexing. The evaluation of the proposed framework is presented for CIFAR-10 dataset 1 by applying individual and combination of different features. Additionally, the primary experimental results with MNIST dataset2 is also presented. © 2010 ACM.

ACM International Conference Proceeding Series

Multiple kernel learning for image indexing

Natural soil deposits commonly exhibit cross-anisotropy about a vertical axis due to their depositional environment. This paper presents a study of the vertical stress distribution in a cross-anisotropic elastic soil deposit due to a point load. The study is based upon the exact solution derived by Liao and Wang (1998) that uses Fourier and Hankel transforms to solve the governing differential equations of the displacement functions. The solution has been first modified to consider a reduced parameter elastic model for cross-anisotropy as proposed by Graham and Houlsby (1983). The vertical stress distribution in the soil has been studied for a vertical point load with a varying degrees of anisotropy. © 2010 ASCE.

Geotechnical Special Publication

Vertical stress under point load on cross-anisotropic elastic half-space with reduced parameter material model

Design of many geotechnical problems, such as the stability of slopes and excavations, are strongly governed by the shear strength of soil represented in three dimensions. In literature, a number of failure criteria have been proposed using isotropic invariant of stress tensor in three dimensional stress spaces. For a linearly pressure-dependent material, there are four basic failure criteria which have been commonly used to describe the behavior; Mohr-coulomb, Drucker - Prager (1952), Lade and Duncan (1975), and Matsuoka and Nakai (1985). Mohr-Coulomb criterion is defined in a 2-D stress space and it follows plane strain condition. The other three which are 3-D failure criteria have been considered during this study for analysis. Calibration of such a model is relatively easy when the tests are performed in axisymmetric conditions and principal stresses are applied on the specimen, e.g. triaxial tests. This paper will present the solutions for calibrating such failure criteria assuming associative flow rule and using the shear strength parameter (ps) obtained from the laboratory tests performed under plane strain conditions e.g. Direct Shear and Simple Shear Test. © 2010 ASCE.

Calibration of 3-D failure criteria for soils using plane strain shear strength data

Zn 0.9Cd 0.1S nanoparticles doped with 0.005-0.24 M cobalt have been prepared by co-precipitation technique in ice bath at 280 K. For the cobalt concentration &gt;0.18 M, XRD pattern shows unidentified phases along with Zn 0.9Cd 0.1S sphalerite phase. For low cobalt concentration (≤0.05 M) particle size, d XRD is ~3.5 nm, while for high cobalt concentration (&gt;0.05 M) particle size decreases abruptly (~2 nm) as detected by XRD. However, TEM analysis shows the similar particle size (~3.5 nm) irrespective of the cobalt concentration. Local strain in the alloyed nanoparticles with cobalt concentration of 0.18 M increases ~46% in comparison to that of 0.05 M. Direct to indirect energy band-gap transition is obtained when cobalt concentration goes beyond 0.05 M. A red shift in energy band gap is also observed for both the cases. Nanoparticles with low cobalt concentrations were found to have paramagnetic nature with no antiferromagnetic coupling. A negative Curie-Weiss temperature of -75 K with antiferromagnetic coupling was obtained for the high cobalt concentration. © 2009 to the authors.

Nanoscale Research Letters

Influence of cobalt doping on the physical properties of Zn 0.9Cd 0.1S Nanoparticles

We propose knowledge based versions of a relatively new family of SVM algorithms based on two non-parallel hyperplanes. Specifically, we consider prior knowledge in the form of multiple polyhedral sets and incorporate the same into the formulation of linear Twin SVM (TWSVM)/Least Squares Twin SVM (LSTWSVM) and term them as knowledge based TWSVM (KBTWSVM)/knowledge based LSTWSVM (KBLSTWSVM). Both of these formulations are capable of generating non-parallel hyperplanes based on real-world data and prior knowledge. We derive the solution of KBLSTWSVM and use it in our computational experiments for comparison against other linear knowledge based SVM formulations. Our experiments show that KBLSTWSVM is a versatile classifier whose solution is extremely simple when compared with other linear knowledge based SVM algorithms. © 2010 Elsevier Inc. All rights reserved.