(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 development of cleaner and renewable energy sources are necessary so that fossil fuel dependency and global warming can be reduced. Present communication is an attempt to explore the available literature on Photovoltaic Thermal (PVT) air collectors and PVT air collector integrated greenhouse drying system. Solar drying is one of the best method to preserve crops for a long time. In developing and under developed countries; per capita electricity production is low; therefore the electricity uses for heating purpose cannot be economically and environmentally justified option. In previous studies, it was found that forced drying is better in terms of controlling drying parameters and PVT air collector is better than standalone PV module in terms of energy storage. In present review paper, combination of PVT air collector and drying system has been discussed. Moreover, thermal modelling of PVT air collector integrated greenhouse drying system has been presented in detail. Average thermal efficiency, electrical efficiency and overall thermal efficiency for PVT air collector are found to be 26.68%, 11.26% and 56.30% respectively at 0.01 kg/s mass flow rate of air. This review paper may be very helpful for researchers and scientists to develop thermal models for different hybrid solar systems. © 2018 Elsevier Ltd

Mechanical Engineering

World University root node

Renewable and Sustainable Energy Reviews

PVT air collector integrated greenhouse dryers

An acceptor-donor-acceptor (A-D-A) triad based on a BODIPY acceptor and a benzodithiophene donor exhibited dual fluorescence and pronounced fluorescence solvatochromism because of twisted intramolecular charge transfer (TICT) state formation. Furthermore, it showed a Stokes shift of ∼194 nm which is the highest known for any BODIPY compound with a readily tunable fluorescence and a high charge carrier mobility of 4.46 × 10-4 cm2 V-1 s-1. © 2018 The Royal Society of Chemistry.

Electrical Engineering

Fulltext

Organic and Biomolecular Chemistry

Dual emissive bodipy-benzodithiophene-bodipy TICT triad with a remarkable Stokes shift of 194 nm

Growing interest in hybrid organic-inorganic lead halide perovskites has led to the development of various perovskite nanowires (NWs), which have potential use in a wide range of applications, including lasers, photodetectors, and light-emitting diodes (LEDs). However, existing nanofabrication approaches lack the ability to control the number, location, orientation, and properties of perovskite NWs. Their growth mechanism also remains elusive. Here, we demonstrate a micro/nanofluidic fabrication technique (MNFFT) enabling both precise control and in situ monitoring of the growth of perovskite NWs. The initial nucleation point and subsequent growth path of a methylammonium lead iodide-dimethylformamide (MAPbI3·DMF) NW array can be guided by a nanochannel. In situ UV-vis absorption spectra are measured in real time, permitting the study of the growth mechanism of the DMF-mediated crystallization of MAPbI3. As an example of an application of the MNFFT, we demonstrate a highly sensitive MAPbI3-NW-based photodetector on both solid and flexible substrates, showing the potential of the MNFFT for low-cost, large-scale, highly efficient, and flexible optoelectronic applications. © 2018 American Chemical Society.

Chemical Engineering

ACS Nano

Nanochannel-Assisted Perovskite Nanowires: From Growth Mechanisms to Photodetector Applications

This paper presents a novel approach to estimate the maximum power point (MPP) of a photovoltaic (PV) array. The MPP of the PV array is directly estimated from the current-voltage (I-V) curve by using Improved Bisection Method (IBM) under different irradiation and temperature conditions. The five parameters single diode model PV module parameters are estimated from the data sheet values given by the manufacturer under standard test condition (STC). The IBM is simple, fast and returns the MPP more accurately. The estimation of MPP of a PV array under different environmental conditions is presented by using MATLAB program. Also, a comparison of the proposed method with different existing methods has been presented for tracking of MPP of the PV array. It is observed that the estimated MPP of the module is nearly equal to the actual MPP values and thus the performance of the proposed method is more accurate. © 2018 IEEE.

ITEC Asia-Pacific 2018 - 2018 IEEE Transportation Electrification Conference and Expo, Asia-Pacific: E-Mobility: A Journey from Now and Beyond

Maximum Power Point Estimation of a PV Array by Using Improve Bisection Method

IoT devices generate data at a remarkable speed which requires near real-time processing. Such need has inspired a new computing paradigm that advocates moving computation to the edge, closer to where data is generated for ensuring low-latency and responsive data analytics. This paper aims at monitoring indoor environment parameters inside the classroom in real time and estimate the occupancy of that room based on the collected data This is done by measuring different environmental parameters like temperature, CO2 etc. and then by performing regression on the collected data. For the purpose of real time monitoring an android application is used which uses MQTT for communication with the edge node. The estimation is then verified against the actual attendance in the classroom at that duration and it gives accuracy between 90\%-95\%. © 2018 IEEE.

Computer Science and Engineering

14th International Conference on Information Processing: Internet of Things, ICInPro 2018 - Proceedings

Occupancy Estimation Using Sensor Data Analytics

The topical stance detection problem addresses detecting the stance of the text content with respect to a given topic: whether the sentiment of the given text content is in favor of (positive), is against (negative), or is none (neutral) towards the given topic. Using the concept of attention, we develop a two-phase solution. In the first phase, we classify subjectivity - whether a given tweet is neutral or subjective with respect to the given topic. In the second phase, we classify sentiment of the subjective tweets (ignoring the neutral tweets) - whether a given subjective tweet has a favor or against stance towards the topic. We propose a Long Short-Term memory (LSTM) based deep neural network for each phase, and embed attention at each of the phases. On the SemEval 2016 stance detection Twitter task dataset [7], we obtain a best-case macro F-score of 68.84% and a best-case accuracy of 60.2%, outperforming the existing deep learning based solutions. Our framework, T-PAN, is the first in the topical stance detection literature, that uses deep learning within a two-phase architecture. © Springer International Publishing AG, part of Springer Nature 2018.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Topical stance detection for twitter: A two-phase LSTM model using attention

We propose a deep learning based technique to classify actions based on Long Short Term Memory (LSTM) networks. The proposed scheme first learns spatial temporal features from the video, using an extension of the Convolutional Neural Networks (CNN) to 3D. A Recurrent Neural Network (RNN) is then trained to classify each sequence considering the temporal evolution of the learned features for each time step. Experimental results on the CMU MoCap, UCF 101, Hollywood 2 dataset show the efficacy of the proposed approach. We extend the proposed framework with an efficient motion feature, to enable handling significant camera motion. The proposed approach outperforms the existing deep models for each dataset. © Springer Nature Singapore Pte Ltd. 2018.

Communications in Computer and Information Science

Recognizing human activities in videos using improved dense trajectories over LSTM

Due to their exceptionally high specific strength and specific stiffness, single-and multiwalled carbon nanotubes (SWCNTs and MWCNTs) are widely used as reinforcement in metallic, ceramic and high-performance polymer matrices. The mechanical properties, including stiffness, strength and bending characteristics, of carbon nanotubes (CNTs) are greatly influenced by a number of factors, including CNT diameter, chirality, number of concentric walls in MWCNTs, chemical functionalization, surface defects and so forth. However, the challenges associated with the separation of a single CNT and its experimental characterization lead to less reliable and varying estimations of mechanical properties. This chapter presents a careful overview of the elastic and inelastic mechanical properties of isolated single-and multiwalled carbon nanotubes, determined using tedious experiments and elaborated computational methods and their dependence on nanotube physical/chemical properties.

Civil Engineering

Carbon Nanotube-Reinforced Polymers: From Nanoscale to Macroscale

Mechanical properties of isolated carbon nanotube

The authors regret that the sources from which the RfC (reference concentration) and the IUR (inhalation unit risk) values were obtained for estimation of RfD (reference dose, presented in Table 2) and SF (slope factor, presented in Table 3) were not clearly indicated in the published article due to an oversight. The revised tables with improved clarity are given below. [Table presented] The authors apologize for any inconvenience caused. © 2018 Elsevier Ltd

Atmospheric Environment

Corrigendum to “Chemical composition and acidity of size-fractionated inorganic aerosols of 2013–14 winter haze in Shanghai and associated health risk of toxic elements” [Atmos. Environ. (2015) 259–271](S1352231015303952)(10.1016/j.atmosenv.2015.09.053)