(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

The paper proposes a motion-based technique to detect persons in a low-resolution video, where the persons look like tiny blobs. The tiny blob-like appearance of the persons are due to camera position which is at a distance from the person(s). The proposed technique uses integral matrix based different spatial and temporal features. Gradient weighted optical flow (GWOF) is calculated for each frame of the video clip to minimize background noise. Spatial filters are used to extract motion features from the GWOF based integral matrices. The combination of image gradient and GWOF features extracts static and moving persons present in the video. The AdaBoost learning technique is used for training. The training is performed using features derived from the positive samples of bounding boxes in a video frame containing a person and negative samples with bounding boxes without a person. The proposed technique is applied on benchmark Tower dataset, UT-Interaction dataset and PETS 2007 dataset. We have obtained approximately 2 to 10 % improvement in the performance compared to the states-of-the-art. © 2014, Springer Science+Business Media New York.

Computer Science and Engineering

World University root node

Multimedia Tools and Applications

A motion-based approach to detect persons in low-resolution video

A new yet simple transformation is proposed to significantly improve the accuracy of computational fluid dynamics (CFD) modeling and simulations of free radical polymerization (FRP) reactions carried out especially in flow microreactors. The new transformation makes the kinetic rate coefficients dimensionless in terms of concentration. To that extent, the chemical data (chemical species concentration and kinetic rate coefficients values) can be fed in original molar form instead of usual mass form to CFD software package while simulating chemical species as passive scalars. The normalization of various variables (passive scalars) helps in reducing the numerical stiffness as well as numerical errors during simulations. Another advantage of this new transformation is that the expression for transformed reaction rate equations remains unchanged thus enabling an easy coding and debugging process. The new transformation was first validated through numerical simulation against theoretical analytical solution of FRP for homogeneous batch reactor. It was then validated through CFD simulation against published experimental data for FRP in coiled tube microreactor under steady-state flow condition. It has also been demonstrated that in CFD simulations of FRP in flow microreactors, significant error arises for the prediction of number-average chain length (and thus $${\text{MW}}_{n}$$MWn, number-average molecular weight) from the use of chemical data in mass form instead of original molar form. This new transformation is thus found to be more suitable for CFD simulations in flow reactors compared to previous Zhu’s transformation. © 2014, Springer-Verlag Berlin Heidelberg.

Chemical Engineering

Microfluidics and Nanofluidics

New transformation proposed for improving CFD simulation of free radical polymerization reactions in microreactors

Asymptotically-accurate dimensional reduction from three to two dimensions and recovery of 3-D displacement field of non-prestretched dielectric hyperelastic membranes are carried out using the Variational Asymptotic Method (VAM) with moderate strains and very small ratio of the membrane thickness to its shortest wavelength of the deformation along the plate reference surface chosen as the small parameters for asymptotic expansion. Present work incorporates large deformations (displacements and rotations), material nonlinearity (hyperelasticity), and electrical effects. It begins with 3-D nonlinear electro-elastic energy and mathematically splits the analysis into a one-dimensional (1-D) through-the-thickness analysis and a 2-D nonlinear plate analysis. Major contribution of this paper is a comprehensive nonlinear through-the-thickness analysis which provides a 2-D energy asymptotically equivalent of the 3-D energy, a 2-D constitutive relation between the 2-D generalized strain and stress tensors for the plate analysis and a set of recovery relations to express the 3-D displacement field. Analytical expressions are derived for warping functions and stiffness coefficients. This is the first attempt to integrate an analytical work on asymptotically-accurate nonlinear electro-elastic constitutive relation for compressible dielectric hyperelastic model with a generalized finite element analysis of plates to provide 3-D displacement fields using VAM. A unified software package 'VAMNLM' (Variational Asymptotic Method applied to Non-Linear Material models) was developed to carry out 1-D non-linear analysis (analytical), 2-D non-linear finite element analysis and 3-D recovery analysis. The applicability of the current theory is demonstrated through an actuation test case, for which distribution of 3-D displacements are provided. © 2014 Elsevier Ltd. All rights reserved.

Mechanical Engineering

International Journal of Engineering Science

Dielectric elastomers: Asymptotically-correct three-dimensional displacement field

Link prediction is a very well studied problem as it has applications in different areas. Many algorithms have been presented in the literature for link prediction problem. The link prediction problem can be explained as follows: given the topology of graph G at a certain time t, we need to predict the topology of the graph at time t′ where t′ > t. The techniques used for link prediction are categorized as follows: nodes based techniques, Link based techniques and path based techniques. There are some other techniques that use meta-approaches. In this paper we present a new algorithm for link prediction on social networks. The algorithm tries to identify nodes that may get deleted by time t′ and use this information to predict new links that might appear in the future. Our tests show that our algorithm shows better result for link prediction on social networks compared to the previous algorithms. We had implemented our algorithm in C# on Pentium Core 2 Duo processor. The data used for testing is Gnutella peer to peer network. © 2014, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.

International Journal of Systems Assurance Engineering and Management

Elimination based algorithm for link prediction on social networks

The severe winter haze episode that occurred in Shanghai from December 2013 to January 2014, characterized by elevated levels of particulate matter (PM), received considerable international attention because of its impacts on public health and disruption of day-to-day activities. To examine the characteristics of PM during this haze episode and to assess the chemistry behind formation of secondary inorganic aerosols (SIA) and associated health impacts due to exposure of toxic elements, we characterized eight water soluble inorganic (WSI) ions and twenty four trace elements in twelve size-fractionated PM (10 nm-9.9 μm). The average mass concentrations of coarse (1.8 μm &lt; Dp &lt; 9.9 μm), fine (Dp &lt; 2.5 μm), ultrafine (0.01 μm &lt; Dp &lt; 0.10 μm) and nano (0.01 μm &lt; Dp &lt; 0.056 μm) particles during hazy days were 2.8, 5.2, 5.3 and 5.1 times higher than those during non-hazy days, respectively. The in-situ pH (pHIS), as predicted by the Aerosol Inorganic Model (AIM-IV) in all sizes of PM, was observed to be lower during hazy days (average of -0.64) than that during non-hazy days (average of -0.29); there was an increased acidity in haze aerosols. Based on the measured concentrations of particulate-bound toxic elements, health risk assessment was conducted, which revealed that the excess lifetime carcinogenic risk to individuals exposed to fine particles under haze events increased significantly (P &lt; 0.05) to 69 ± 18 × 10-6 compared to non-hazy days (34 ± 10 × 10-6). The qualitative source attribution analysis suggested that the occurrence of haze could be due to a combination of increased emissions of PM from multiple anthropogenic sources followed by its accumulation under unfavourable meteorological conditions with lower mixing heights and less wind speeds and the formation of secondary aerosols. © 2015 Elsevier Ltd.

Civil Engineering

Atmospheric Environment

Chemical composition and acidity of size-fractionated inorganic aerosols of 2013-14 winter haze in Shanghai and associated health risk of toxic elements

An optimized protocol for induction and establishment of Agrobacterium rhizogenes-mediated hairy root cultures of Plumbago zeylanica L. was developed through selection of suitable explant type and the bacterial strain. The infection of internodal explants from an in vivo plant and leaves of in vitro origin with the A4 strain resulted in the emergence of hairy roots at a transformation frequency of 86.33 and 42.33 %, respectively. Independent transformed root somaclones (rhizoclones) capable of sustained growth were maintained under a low illumination in auxin-free agar-solidified Murashige and Skoog (MS) medium through subcultures at periodic intervals. The presence of pRi TL-DNA rolB or rolC genes and pRi TR-DNA mas2 gene in the transformed rhizoclone genome was ascertained by PCR amplification. Concentrations and type of carbon source, auxin and media strength were optimized for root biomass growth. Five independent rhizoclones each from A4- and LBA9402-transformed root lines were studied for their plumbagin accumulation at different growth phases, using HPLC analysis. The potential for plumbagin biosynthesis was expressed in all the tested rhizoclones, although distinct inter-clonal variations were noted. It was evident that maturation of hairy roots was more important for plumbagin accumulation; slow-growing and early-maturing rhizoclones accumulated more plumbagin compared to fast-growing and late-maturing rhizoclones. A4-induced rhizoclone HRA2B5 was identified as the most superior clone with a higher plumbagin yield potential in comparison with other tested hairy root clones, in vitro-grown non-transformed roots and in vivo roots of naturally occurring P. zeylanica. © 2014, Springer Science+Business Media New York.

Applied Biochemistry and Biotechnology

High-Performance Liquid Chromatographic Quantification of Plumbagin from Transformed Rhizoclones of Plumbago zeylanica L.: Inter-Clonal Variation in Biomass Growth and Plumbagin Production

Environmental monitoring using external and Smartphone-interfaced wireless sensors has been widely used in the past. The roadblocks start emerging when we use on-board sensors in off-the-shelf Smartphones to estimate context aware environmental parameters like ambient temperature, humidity and atmospheric pressure. In this work, we evaluate the sensitivity and accuracy of the on-board ambient temperature sensor under various circumstances and measure its performance against standardized weather monitoring equipment. Additionally, we identify the roles of several internal and external factors that affect the temperature data. Such an investigation is motivated by the need of pervasive temperature sensing to power Smart HVAC environments and for weather crowdsourcing. Our experiments reveal that while the on-board temperature sensors have great potential, using them for large scale data collection still requires significant work. © 2015 IEEE.

Life Sciences

(SoNS) School of Natural Sciences

2015 7th International Conference on Communication Systems and Networks, COMSNETS 2015 - Proceedings

Contextual sensitivity of the ambient temperature sensor in Smartphones

An enlargement of the candidate vector set of QR-least reliable layer (QR-LRL) based MIMO detector for efficient soft output generation is proposed. Previous work (Bahng et al. in IEICE Trans Commun, E89–B(10):2956–2960, 2008) shows that the QR-LRL based MIMO detector approaches hard decision output ML performance, but does not match soft output ML performance due to empty candidate vector set problem. Performance degradation is more severe when modulation order is low. Some of the previous methods have provided solutions to empty vector set (EVS) problem (Kawai et al. in IEICE Trans Commun, E88–B(1):47–57, 2005; Bahng et al. in IEICE Trans Commun, E89–B(10):2956–2960, 2008; Kim et al. in IEICE Trans Commun, E92–B(11):3512–3515, 2009), but are not efficient in terms of performance or computation complexity. In this paper, we enlarge the candidate vector set of QR-LRL detector by applying every constellation point at each layer. The proposed detector thus effectively solves the EVS problem and achieves soft ML performance while keeping the computation complexity low, especially at low modulation order. © 2015, Springer Science+Business Media New York.

Electrical Engineering

Wireless Personal Communications

Mitigating Empty Vector Set Using Enlarged QRLRL-M Soft SM-MIMO Detector

A statistical model for smooth shapes in Kendall shape space

This work is focused on intermediate pyrolysis of sawdust in a 100. g batch reactor at 500. ±. 10. °C. The pyrolysis vapors coming from reactor were directly quenched with chilled biodiesel from jatropha oil at 4. ±. 2. °C to obtain a suitable blend for stationary engine application. Total bio-oil yield was found to be 37\% (wt.). After layer separation from the resultant mixture, biodiesel miscible bio-oil phase calorific value was found to be 39. ±. 0.5. MJ/kg, which indicated that the bio-oil/biodiesel mixture was stable within the conditions tested and hence suitable for engine applications. The overall process provides a platform for blended biofuel, biochar as substitute of sub-bituminous coal and pyro-gas for combined heating and power application. © 2015 Elsevier B.V.