(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 local descriptors have gained wide range of attention due to their enhanced discriminative abilities. It has been proved that the consideration of multi-scale local neighborhood improves the performance of the descriptor, though at the cost of increased dimension. This paper proposes a novel method to construct a local descriptor using multi-scale neighborhood by finding the local directional order among the intensity values at different scales in a particular direction. Local directional order is the multi-radius relationship factor in a particular direction. The proposed local directional order pattern (LDOP) for a particular pixel is computed by finding the relationship between the center pixel and local directional order indexes. It is required to transform the center value into the range of neighboring orders. Finally, the histogram of LDOP is computed over whole image to construct the descriptor. In contrast to the state-of-the-art descriptors, the dimension of the proposed descriptor does not depend upon the number of neighbors involved to compute the order; it only depends upon the number of directions. The introduced descriptor is evaluated over the image retrieval framework and compared with the state-of-the-art descriptors over challenging face databases such as PaSC, LFW, PubFig, FERET, AR, AT&T, and ExtendedYale. The experimental results confirm the superiority and robustness of the LDOP descriptor. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

World University root node

Computer Science and Engineering

Fulltext

Multimedia Tools and Applications

LDOP: local directional order pattern for robust face retrieval

Bioimplants are susceptible to simultaneous wear and corrosion degradation in the aggressive physiological environment. High entropy alloys with equimolar proportion of constituent elements represent a unique alloy design strategy for developing bioimplants due to their attractive mechanical properties, superior wear, and corrosion resistance. In this study, the tribo-corrosion behavior of an equiatomic MoNbTaTiZr high entropy alloy consisting of all biocompatible elements was evaluated and compared with 304 stainless steel as a benchmark. The high entropy alloy showed a low wear rate and a friction coefficient as well as quick and stable passivation in simulated body fluid. An increase from room temperature to body temperature showed excellent temperature assisted passivity and nobler surface layer of the high entropy alloy, resulting in four times better wear resistance compared to stainless steel. Stem cells and osteoblast cells displayed proliferation and migratory behavior, indicating in vitro biocompatibility. Several filopodia extensions on the cell periphery indicated early osteogenic commitment, and cell adhesion on the high entropy alloy. These results pave the way for utilizing the unique combination of tribo-corrosion resistance, excellent mechanical properties, and biocompatibility of MoNbTaTiZr high entropy alloy to develop bioimplants with improved service life and lower risk of implant induced cytotoxicity in the host body. ©

Mechanical Engineering

ACS Applied Bio Materials

Biocompatible High Entropy Alloys with Excellent Degradation Resistance in a Simulated Physiological Environment

Urban Air Mobility (UAM) is a long-desired service which will revolutionize the present transportation facilities, by introducing air mobility for on-demand aviation. Due to the continuous increase in population, road traffic is increasing at alarming rates and the problem of congestion is also increasing in metro cities. These new services will provide improved ways for individuals to go around urban communities and urban territories while decreasing blockage. eVTOLs are aircraft that are capable of Vertical Take-off and Landing (VTOL) with no requirement of run-up space and are tremendously getting popular when it comes to UAM due to the important factor of clean propulsion with zero-emission. The industry is rapidly proposing and adopting new vehicle concepts to meet consumer demands and hence conceptually designing these vehicles with basic guidelines will set a preliminary foundation for more innovative technologies to come. This research work sets a baseline procedure and an initial iteration example for the industries and upcoming companies in this sector hence focuses on the Conceptual designing of eVTOLs. The novelty of the presented work lies in enhanced eVTOL configuration using coaxial ducted tilt rotors with wings. © 2020 IEEE.

Proceedings of the 4th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2020

Baseline procedure for conceptual designing of an eVTOL for Urban Air Mobility

The present work deals with the nonlinear stability characteristics of geometrically imperfect shear deformable functionally graded plates (FGP) subjected to thermo-mechanical loads. The equilibrium, stability, and compatibility equations are derived using trigonometric shear-strain function based refined shear deformation plate theory. The displacement field used in the present study has been employed for FGP for the first time. The in-plane and transverse displacements consist of bending and shear components, whereas the displacement field contains only four unknowns. Geometric nonlinearity has been incorporated in the formulation in a von-Karman sense. A generalized porosity model has also been developed to accommodate both even and uneven porosity distribution reported in the literature. Various models of geometric imperfection have been modeled using imperfection function. An exact expression for the critical buckling load and critical buckling thermal load of geometrically imperfect porous FGPs for various loading conditions have been developed. After ensuring the excellent accuracy of the developed expression, the influence of geometric imperfection, porosity inclusion, and geometric configuration on the nonlinear stability of FGPs has been discussed extensively. The results presented in this paper will be used as a benchmark for future research. © IMechE 2020.

Journal of Strain Analysis for Engineering Design

Microstructure/geometric imperfection sensitivity on the thermo-mechanical nonlinear stability behavior of functionally graded plates using four variable refined structural kinematics

This paper presents critical assessment of codal provisions to determine lateral stability of a well foundation. A two-dimensional finite element model of soil–well foundation system is developed for this study. The well foundation is modeled as a linear elastic body, whereas the soil as a nonlinear elasto-plastic material which is defined using multi-yield surface plasticity model. Interface between the well foundation and the adjoining soil is defined using constitutive relationships describing relative sliding and separation at the interface. Assumptions considered in the existing codal provisions to determine lateral stability of a well foundation are evaluated in light of the results obtained from the present study. The present study shows that the mechanism of deformation of laterally loaded soil–well foundation system obtained in this study differs from that considered in the existing codal provisions. It is observed that the existing codal provisions overestimate the lateral load capacity of a well foundation. © 2020, Indian Geotechnical Society.

Civil Engineering

Indian Geotechnical Journal

An Assessment of Codal Provisions for Analysis of Laterally Loaded Well foundations

This paper presents an intelligent wind speed sensor less maximum power point tracking (MPPT) method for a variable speed wind energy conversion system (VS-WECS) based on a Q-Learning algorithm. The Q-Learning algorithm consists of Q-values for each state action pair which is updated using reward and learning rate. Inputs to define these states are electrical power received by grid and rotational speed of the generator. In this paper, Q-Learning is equipped with peak detection technique, which drives the system towards peak power even if learning is incomplete which makes the real time tracking faster. To make the learning uniform, each state has its separate learning parameter instead of common learning parameter for all states as is the case in conventional Q-Learning. Therefore, if half learned system is running at peak point, it does not affect the learning of unvisited states. Also, wind speed change detection is combined with proposed algorithm which makes it eligible to work for varying wind speed conditions. In addition, the information of wind turbine characteristics and wind speed measurement is not needed. The algorithm is verified through simulations and experimentation and also compared with perturbation and observation (P&O) algorithm. © 1986-2012 IEEE.

Electrical Engineering

IEEE Transactions on Energy Conversion

Q-Learning based Maximum Power Extraction for Wind Energy Conversion System with Variable Wind Speed

Link prediction in networks has applications in computer science, graph theory, biology, economics, etc. Link prediction is a very well studied problem. Out of all the different versions, link prediction for unipartite graphs has attracted most attention. In this work we focus on link prediction for bipartite graphs that is based on two very important concepts—potential energy and mutual information. In the three step approach; first the bipartite graph is converted into a unipartite graph with the help of a weighted projection, next the potential energy and mutual information between each node pair in the projected graph is computed. Finally, we present Potential Energy-Mutual Information based similarity metric which helps in prediction of potential links. To evaluate the performance of the proposed algorithm four similarity metrics, namely AUC, Precision, Prediction-power and Precision@K were calculated and compared with eleven baseline algorithms. The Experimental results show that the proposed method outperforms the baseline algorithms. © 2020, The Author(s).

Scientific Reports

A potential energy and mutual information based link prediction approach for bipartite networks

There has been exponential growth in the amount of data being generated on a daily basis. Such a huge amount of data creates a need for efficient data storage techniques. Due to the limitations of existing storage media, new storage solutions have always been of interest. There have been recent developments in order to efficiently use synthetic deoxyribonucleic acid (DNA) for information storage. DNA storage has attracted researchers because of its extremely high data storage density, about 1 exabyte/mm3 and long life under easily achievable conditions. This work presents an encoding scheme for DNA-based data storage system with controllable redundancy and reliability, the authors have also talked about the feasibility of the proposed method. The authors have also analysed the proposed algorithm for time and space complexity. The proposed encoding scheme tries to minimise the bases per letter ratio while controlling the redundancy. They have experimented with three different types of data with a value of redundancy as 0.75. In the randomised simulation setup, it was observed that the proposed algorithm was able to correctly retrieve the stored data in our experiments about 94\% of the time. In the situation, where redundancy was increased to 1, the authors were able to retrieve all the information correctly in the proposed experiments. © The Institution of Engineering and Technology 2020.

IET Nanobiotechnology

Encoding scheme for data storage and retrieval on DNA computers

AIAA Journal

Geometric nonlinear analysis of composite stiffened panels using variational asymptotic method

A novel and strategic green energy production method that utilizes relative wind generated from moving vehicles is presented. A speeding train generates an enormous wake of wind around it, which stocks a substantial amount of kinetic energy. In this study, this freely accessible wind power is harvested by installing a modified savonius wind turbine within the slipstream region of the train. A computer-oriented fluid-solid integrate simulation of wind turbine propelled by train-induced wind is performed by executing all physically realistic boundary conditions. The numerical study is based on open-source CFD toolbox OPENFOAM, and the results were validated against benchmark experimental study. Parametric sensitivity analysis such as optimal turbine performance within the slipstream regime, torque prediction from express trains, two opposite crossing trains, tunnel condition, and turbine wind turbine clusters arrangement has been reported. This study enhances the understanding of the power generation by the turbine from the train slipstream which is not reported in any open literature as far as the authors’ present knowledge goes. Copyright © 2020 by ASME