(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 study investigates spatio-temporal paradigm of the impact of road networks on urban ecosystem dynamics (UED) by analysing the composition and configuration of land use land cover (LULC) and land surface temperatures (LST) derived from Landsat data for the years 2000 and 2017. The results indicate a positive association between road network and built-up land showing higher concentration of built-up land closer to the road network. This increase in grey infrastructure has led to an increase in the maximum LST by 6 °C to 7.5 °C along primary and tertiary roads, whereas 4 °C to 5 °C along secondary roads. Rapid intensification of road network along with the associated disproportionate changes in LULC and LST are deemed to be the major contributors to UED. Findings from this study will serve as baseline for examining the influence of road network on regional urban growth and assist in sustainable road infrastructure planning. © 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group.

Civil Engineering

World University root node

Geocarto International

Road network drives urban ecosystems - a longitudinal analysis of impact of roads in the central Himalaya

The solar power tower plant consists of thousands of heliostats, and heliostat field cost contributes nearly 40–50\% of the total plant cost. This makes the cost of heliostat an important parameter while designing solar power tower plant, and it varies considerably with its size and wind loads. Furthermore, the size and aspect ratio of heliostat have a significant influence on the wind loads impacting its load-bearing components. While the importance of optimum size of reflector area has been studied by several researchers, its aspect ratio (width/height) has not been examined in detail. In this view, the main objective of this study is to identify the appropriate aspect ratio of a heliostat’s reflector area. An analysis of heliostat cost using its reflector area and the aspect ratio as variable parameters illustrates that heliostat cost per unit area can be minimized by distributing costs into various categories having different cost dependencies on area as well as aspect ratio. Using the component-wise cost break-up of 148 m2 Advanced Thermal Systems' heliostat as a reference, optimum area and aspect ratio of heliostat are determined parametrically. Further, a hypothetical power tower plant with 50 MW capacity and 6 h of thermal energy storage is simulated with heliostat fields comprising heliostats built with various aspect ratios and corresponding optimum reflector area. The results indicate that it is not only more economical to build heliostats with aspect ratio of around 2, but also such heliostat fields deliver higher optical efficiency on an annualized basis. © 2019, King Fahd University of Petroleum & Minerals.

Mechanical Engineering

Arabian Journal for Science and Engineering

Effect of Aspect Ratio of Heliostat on Cost of Energy from Solar Power Tower Plants

In present communication, environ-economic analysis has been done for PVT drying system in which different types of PV module (c-Si, p-Si or m-Si, a-Si, CdTe, and CIGS) taken into consideration. Environmental feasibility has been explored in terms of CO2 emission, net CO2 mitigation and carbon credit earned based on energy and exergy output of the system on yearly basis. For yearly analysis of PVT system based on energy, input data has been taken from IMD Pune, India. The results showed that CO2 emission is maximum in the case of c-Si and minimum in CIGS manufacturing for given setup, respectively. Further, carbon credit earned has been evaluated based on energy and exergy analysis and found to be minimum and maximum in the case of CIGS and C-Si respectively. © 2020 IEEE.

International Conference on Electrical and Electronics Engineering, ICE3 2020

Environmental Feasibility of PVT Drying System

Traffic congestion has been an emerging issue when it comes to problems faced by commuters on road on a daily basis. It leads to loss of time, money, and fuel when one is stuck in a traffic jam. This has led to the need of more path-breaking technologies in the field of intelligent transport systems (ITS). Today, a lot of data are available which can be used to extract important information and perform the desired analysis. With CCTV surveillance cameras at almost every traffic pole, information like count of vehicles can be used to analyze the traffic patterns at a particular location. In this paper, different methods have been used to get the accurate count of vehicles and their performances have been analyzed. Popular image processing method background subtraction and deep learning algorithms: R-CNN, Fast R-CNN and Faster R-CNN have been implemented. © 2020, Springer Nature Singapore Pte Ltd.

Electrical Engineering

Lecture Notes in Electrical Engineering

Traffic Control Enhancement with Video Camera Images Using AI

Lime-based mortar interlayer plays an important role in structural and architectural construction. Lime mortar undergoes repetitive changes in temperature when it is exposed to its service environment. Change in temperature has a significant effect on the thermal deformation of cement mortar and even affects directly the durability of century decade monuments and structure under extreme regions. This paper deals with thermal deformation of lime mortar, which is the prime constituent of cement and the oldest construction material by measuring its deformed geometrical configuration. In the first part, it is aimed to investigate the thermal deformation of mortar cube, its changes in length and mass of the specimens continuously measured during the heating and cooling cycles within the range of temperatures of −20 to 70 °C. The second part of this paper aims to investigate the pore formation and pore size distrubution in lime and lime mortar sample using optical microscopic images. Although a careful visual inspection can provide very good accuracy information, it has inherent limitations in assessing the structural integrity, and also, visual inspection can provide limited information to a damaged facility. In this paper, a detailed pore distribution analysis has done using digital image processing tool for better interpretation of thermal damages in lime mortar. The above-proposed tool can be used as aided tool for retrofitting and conservation of many architectural heritages. © Springer Nature Singapore Pte Ltd. 2020.

Lecture Notes in Civil Engineering

Thermal and Optical Investigation of Lime Mortar for Repetitive Thermal Loading

The widespread deployment of multi-biometrics to authenticate users prompts the need for biometric systems with high recognition performance. Further, the biometric data, once leaked or stolen, remains compromised forever. Hence biometric security is of utmost importance. Existing biometric template protection schemes either degrade the recognition performance or they have issues with security and speed. We propose a cancelable multi-biometric authentication approach where a novel bit-wise encryption scheme transforms a biometric template to a protected template using a secret key generated from another biometric template. It fully preserves the number of bit-errors in the original and the protected template to ensure recognition performance equivalent to the performance of the unprotected systems. We introduce Algorithm I and Algorithm II for bit-wise encryption; both are defined over cryptographic-primitives- block cipher based encryption and keyed-hash function. We profile these algorithms on various hardware architectures to calculate the efficiency in terms of the time taken during enrolment and authentication phase. For Algorithm II, we observe that a 3.3 GHz desktop architecture takes about 18 milliseconds on an average of over 200 runs to authenticate a user. Additionally, we provide mathematical proof to show that the proposed scheme guarantees secrecy and irreversibility. The results of comparisons with the existing biometric template protection schemes on the various face and iris databases show that the proposed work provides significantly good recognition performance and efficiency, while it achieves high security. Finally, the bit-wise encryption scheme can be built over the commercial-off-the-shelf systems to achieve security with equivalent high performance. © 2005-2012 IEEE.

Computer Science and Engineering

IEEE Transactions on Information Forensics and Security

Cancelable Multi-Biometric Approach Using Fuzzy Extractor and Novel Bit-Wise Encryption

In recent years, orientation and navigation technologies and support for people with visually impaired disabilities have increased. This paper proposes a model for the detection of objects for visually impaired individuals. We have developed a module for blind people to identify and match items scanned to a list of objects, such as currency notes, person and bottle, and the angle and distance of the object being detected from the camera. The model is based on image recognition from a database of objects. The results of the image recognition shall be communicated to the user by system audio feedback. © 2020 IEEE.

2020 IEEE Region 10 Symposium, TENSYMP 2020

Object and Currency Detection with Audio Feedback for Visually Impaired

In this article, we introduce two types of real-valued sums known as Complex Conjugate Pair Sums (CCPSs) denoted as CCPS^{(1)} and CCPS^{(2)}, and discuss a few of their properties. Using each type of CCPSs and their circular shifts, we construct two non-orthogonal Nested Periodic Matrices (NPMs). As NPMs are non-singular, this introduces two non-orthogonal transforms known as Complex Conjugate Periodic Transforms (CCPTs) denoted as CCPT^{(1)} and CCPT^{(2)}. We propose another NPM, which uses both types of CCPSs such that its columns are mutually orthogonal, this transform is known as Orthogonal CCPT (OCCPT). After a brief study of a few OCCPT properties like periodicity, circular shift, etc., we present two different interpretations of it. Further, we propose a Decimation-In-Time (DIT) based fast computation algorithm for OCCPT (termed as FOCCPT), whenever the length of the signal is equal to 2^v, v in mathbb {N}. The proposed sums and transforms are inspired by Ramanujan sums and Ramanujan Period Transform (RPT). Finally, we show that the period (both divisor and non-divisor) and frequency information of a signal can be estimated using the proposed transforms with a significant reduction in the computational complexity over Discrete Fourier Transform (DFT). © 1991-2012 IEEE.

Fulltext

IEEE Transactions on Signal Processing

Orthogonal and Non-Orthogonal Signal Representations Using New Transformation Matrices Having NPM Structure

Selective feature extraction from single-channel electroencephalogram signal provides appropriate classification of mental tasks, which is crucial for designing mobile brain-computer interface and neuro-bio-feedback systems. However, existing features deteriorate in the presence of artifacts. Therefore, we propose a mental task classification method using variational mode decomposition (VMD)-based novel feature extraction from single-channel EEG, with three stages: Signal decomposition using VMD; computation of proposed variational mode energy ratio; classification using adaptive boosting algorithm. The proposed method is evaluated using artifact-free and contaminated EEG signals from EEG during mental arithmetic task (EEGMAT) database and self-acquired (SA) database recorded using single-channel device. Average subject-specific accuracies of 93\% and 96\% for classification of baseline and serial-subtraction task have been achieved in EEGMAT and SA databases respectively. Extensive comparative analysis exhibits the superiority of proposed feature as compared to existing features in terms of accurate classification of baseline-mental task, and robustness under artifactual EEG signals. © 2020 IEEE.

2020 IEEE 17th India Council International Conference, INDICON 2020

Variational Mode Decomposition Based Mental Task Classification from Electroencephalogram

Resistive Random Access Memories (RRAMs) or Memristor has been a revolution in current nonvolatile memory technology. This work demonstrates an analytical model that shows the effect of applied bias on the metal-semiconductor interface to affect resistive switching of an RRAM device. The applied bias modulates the corresponding interface in terms of various interfacial electrical parameters. Besides, the change in bias affects the distribution of bulk defects primarily oxygen vacancies as well as non-lattice oxygen ions. This, in turn, also affects the corresponding resistance of bulk as well as other electrical parameters at the interface. Further conduction mechanism of the device with interfacial oxide formation as well as dissolution to impact resistive switching behavior has been elaborated. © 2020 IEEE.