(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

With the wide spread usage of LBS, convenience has reached on the finger tips of mobile users, but on the other side, it has escalated many security and privacy concerns. In this paper we address the location K-anonymity problem using fuzzy spatio-temporal attributes, a new perspective of looking at privacy issue in location privacy. In the context of LBSs and mobile clients, location K-anonymity refers to K-anonymous usage of location information. A novel approach for determining location disclosure based on fuzzy attributes of spatio-temporal context is proposed which in turn will give us a value of K for K-anonymity purpose. Spatio-temporal fuzzy attributes for privacy issues are identified and Fuzzy Inference System (FIS) is implemented that takes these attributes as input and generates location disclosure value. Using Location disclosure value, K is computed for K-anonymity to ensure privacy. This value of K is directly based on current spatio temporal context and is valid for all users present in that context. Further, an exhaustive rule base of fuzzy rules is generated based on responses obtained by conducting survey on the potential users who frequently use POI (Point of Interest) services. Later on, fuzzy rules for FIS rule base are extracted using Fuzzy C Means (FCM) clustering technique. Using the rules extracted through FCM, the size of rule base is reduced and the performance of the FIS is evaluated. Number of rules in rule base is decreased for scalability and efficiency purposes. Root Mean Square Error (RMSE) for every reduced set is computed and compared with initial exhaustive rule base. It is observed that size of rule base can be decreased to a considerable extent. © 2014 IEEE.

World University root node

Computer Science and Engineering

Proceedings - IEEE International Conference on Mobile Data Management

K anonymity based on fuzzy spatio-temporal context

We investigated the influence of nanoscale pattern shapes, contours, and surface chemistry on wetting behavior using a combination of experimental and modeling approaches. Among the investigated topographical shapes, re-entrant geometries showed superior performance owing to their ability to restrain the liquid-air interface in accordance with Gibbs criteria. The wetting state is also controlled by the surface texture in addition to the surface chemistry. Topographies with smaller intrinsic angles are better able to support the liquid droplet. Based on these observations, two geometrical relationships for designing superhydrophobic patterns exhibiting the Cassie-Baxter state are proposed. A detailed analysis of the simulation results showed the presence of viscous forces during the initial transient phase of the droplet interaction with the solid surface even at negligible normal velocity, which was verified experimentally using a high-speed imaging technique. During this transient phase, for a polystyrene surface, the liquid front was observed to be moving with a radial velocity of 0.4 m s-1, which gradually decreased to almost zero after 35 ms. We observed that the viscous energy dissipation density is influenced by the surface material and topography and the wetting state. The viscous energy dissipation density is minimal in the case of the Cassie-Baxter state, while it becomes quite significant for the Wenzel state. The viscous effects are reduced for topographies with smooth geometries and surfaces with high slip length. This journal is © The Royal Society of Chemistry.

Mechanical Engineering

Fulltext

Nanoscale

Effect of topography on the wetting of nanoscale patterns: Experimental and modeling studies

An in situ composite coating on pure aluminium substrate was prepared by novel microwave processing of iron based metallic glass powder precursor. The microstructure obtained after processing comprised of a molybdenum rich harder phase uniformly distributed in iron rich softer phase. The hardness and modulus of each phase were obtained by nanoindentation. Scratch test across the substrate coating indicated good interface strength and strong adhesion of the coating with the substrate. © 2014 Institute of Materials, Minerals and Mining.

Surface Engineering

Microwave assisted in situ composite coating using metallic glass precursor

This chapter presents a comprehensive study on the influence of friction stir processing/welding (FSW/FSP) on corrosion behaviour. It briefly discusses the different aspects of corrosion including corrosion types, measurement techniques and data analysis. The corrosion behaviour of a wide range of friction stir processed materials, including light weight metals such as magnesium and aluminum alloys, as well as high strength metals such as steel, has been discussed in detail. The influence of FSP parameters on the microstructural evolution, comprising grain-size and precipitate refinement along with its correlation with the corrosion properties, has been described for different materials. © 2014 The authors and contributors. All rights reserved.

Advances in Friction-Stir Welding and Processing

Corrosion behaviour in friction stir processed and welded materials

Friction stir processing (FSP) was carried out for AE42 Mg alloy resulting in significant grain refinement and uniform dispersion of fine in situ precipitates. The average grain size was 20°μm for the as-cast AE42 alloy, which was refined to 1.5°μm after FSP. Tensile testing revealed significantly higher modulus and yield strength for the friction stir processed (FSPed) specimen with some improvement in ductility. The fractured surface of the as-cast alloy showed ridges, grooves and cracks indicating brittle failure. In contrast, the fractured surface of FSPed specimen showed fine dimples, characteristic of ductile failure. Nano-indentation was used to analyze the variation of hardness and modulus across the nugget zone of the FSPed specimen. FSPed specimen demonstrated greater strain-hardening tendency compared to the as-cast alloy. Enhancing the mechanical properties of Mg alloys can result in substantial cost savings across a number of industries and have wide economic impact. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advanced Engineering Materials

Enhancing the mechanical properties of AE42 magnesium alloy through friction stir processing

We demonstrate the refinement and uniform distribution of the crystalline dendritic phase by friction stir processing (FSP) of titanium based in situ ductile-phase reinforced metallic glass composite. The average size of the dendrites was reduced by almost a factor of five (from 24 μm to 5 μm) for the highest tool rotational speed of 900 rpm. The large inter-connected dendrites become more fragmented with increased circularity after processing. The changes in thermal characteristics were measured by differential scanning calorimetry. The reduction in crystallization enthalpy after processing suggests partial devitrification due to the high strain plastic deformation. FSP resulted in increased hardness and modulus for both the amorphous matrix and the crystalline phase. This is explained by interaction of shear bands in amorphous matrix with the strain-hardened dendritic phase. Our approach offers a new strategy for microstructural design in metallic glass composites. © 2014 National Institute for Materials Science.

Science and Technology of Advanced Materials

Controlling the length scale and distribution of the ductile phase in metallic glass composites through friction stir processing

The estimation of Maximum Power Point (MPP) of photovoltaic (PV) array is essential for integration of solar power to microgrid. This paper presents the estimation of Maximum Power Point of a solar photovoltaic array under different environmental conditions (i.e. different temperature and solar irradiation) using Levenberg Marquardt method. The estimation is done using the single diode based model parameters of photovoltaic (PV) module. The photovoltaic (PV) module parameters are estimated from the data sheet values given by manufacturer. The estimated Maximum Power Point (MPP) values of the PV array under different environmental condition are presented in the simulated current-voltage and power-voltage characteristics. It is demonstrated that the estimated MPP values of the PV array are nearly equal to simulated MPP values. © 2014 IEEE.

Electrical Engineering

2014 IEEE Innovative Smart Grid Technologies - Asia, ISGT ASIA 2014

Estimation of Maximum Power Point of PV array using datasheet values for microgrid integration

We consider a two-user binary multiple access setup suitable for pulse based communications. The link from each user to the receiver is modeled by independent time-varying Z-channel. We consider the cross-over probabilities of the Z-channels as the state of the process. Each user has access only to its own state process and is unaware of the other user's states. The receiver observes the superposition of the symbols from the links. Assuming a block fading state process, we propose adaptive communication schemes, which also ensure outage-free communication in any transmission block. Furthermore, the proposed strategies turn out to be throughput optimal for highly dispersive systems. {\textcopyright} 2014 IEEE.

2014 20th National Conference on Communications, NCC 2014

MAC channel with states for pulse-based communication systems

Thermal diffusivity of anodic alumina (AAO) templated bismuth telluride nanowires has been measured using recently proposed frequency modulated thermal wave imaging (FMTWI). The technique provides a fast and efficient non-contact approach for in-plane thermal characterization of nanomaterials. An intensity modulated up-chirp signal is applied as photothermal excitation and the thermal response is monitored using an infrared (IR) thermography based temperature sensing system. Thermal diffusivity of the sample is experimentally assessed using the multiple phase information extracted from a single run of the experiment. This feature considerably reduces the operational time of the experiment as compared to similar lock-in thermography based approaches. This unique approach of solely using the phase information for thermal diffusivity measurements, allows the experiment to be more immune to the local variations in surface temperature and emissivity of the radiating surface. The experimental details of the technique are discussed, with practical measurement of thermal diffusivity of Bi2Te3/AAO nanocomposite in direction perpendicular to the nanochannel axis. © 2014 SPIE.

Proceedings of SPIE - The International Society for Optical Engineering

Thermal diffusivity estimation of templated nanocomposite using frequency modulated infrared imaging

Reinforcement learning (RL) algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, neural network function approximators suffer from a number of problems like learning becomes difficult when the training data are given sequentially, difficult to determine structural parameters, and usually result in local minima or overfitting. In this paper, a novel on-line sequential learning evolving neural network model design for RL is proposed. We explore the use of minimal resource allocation neural network (mRAN), and develop a mRAN function approximation approach to RL systems. Potential of this approach is demonstrated through a case study. The mean square error accuracy, computational cost, and robustness properties of this scheme are compared with static structure neural networks. © Springer International Publishing Switzerland 2014.