(SoE) School of Engineering

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Shiv Nadar University

This paper proposes the precoder for Multi User-MassiveMIMO (MU-MaMI) frequency selective broadcast channels with few User Terminals(UTs) having single antenna each. The frequency selective effect of the MaMI channel will be manifested as ISI and IUI. In order to mitigate these interferences and to eliminate the group level decoding of UTs, a precoder is proposed utilizing the block time Channel Impulse Responses (CIRs). This proposed precoder is designed based on the following approaches, Matched Filter(MF), Zero Forcing (ZF), Minimum Mean Square Error (MMSE) and Regularized Channel Inversion (RCI). The performance of these precoders is evaluated using single symbol time (one time symbol) and block time symbols (N time symbols) of each UT. The optimal length N block time symbols and minimum number of Base Station (BS) antennas required for a given N block time and multipath L is evaluated with respect to the Signal-to-Interference Noise Ratio (SINR) asymptotic limits. © 2017 IEEE.

Electrical Engineering

Proceedings of the 2017 International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2017

Space-time block based linear precoders for multi user-MassiveMIMO frequency selective broadcast channels

This paper deals with permutation flow shop scheduling problem in which an integrated cost model consisting of work-in-process inventory carrying cost and penalty cost due to batch delay is proposed. The objective is to obtain an optimum production schedule which minimizes the expected total cost per unit time of scheduling. To optimize the objective function, we apply two new metaheuristic optimization techniques namely TLBO (teaching-learning based optimization) and Jaya and two traditional algorithms: PSO (particle swarm optimization) and SA (simulated annealing). The problem is solved for several instances ranging from 8 jobs and 5 machines to 500 jobs and 20 machines. Computational results show that for small instances, all algorithms performed equally good when compared with the exact solution (total enumeration method). However, for medium and large size problems, enumeration method was unable to give the results in a reasonable computation time period. Therefore the results of all four algorithms are compared among themselves and found that Jaya outperforms all algorithms. However, for a few large instances, SA yields better results in less computation time as against other heuristics. The overall performance of all algorithms reveals that TLBO and Jaya have considerable potential to solve discrete combinatorial problems such as permutation flow-shop scheduling problems. © 2018 Elsevier Ltd

Mechanical Engineering

Computers and Industrial Engineering

A TLBO and a Jaya heuristics for permutation flow shop scheduling to minimize the sum of inventory holding and batch delay costs

Opportunistic maintenance (OM) models take the opportunity of economic dependencies among components in the system when it stops due to failure or scheduled preventive maintenance (PM) of a certain equipment. Performing maintenance actions simultaneously can substantially bring down the maintenance costs in terms of reduced downtime costs, production losses, service and labor costs, etc. However, maintaining all components together may be uneconomical due to over or underutilization. Secondly, most of the study on opportunistic maintenance consider the system comprising of either multi-machines with the single component or single machine with multi-components. Based on this motivation, the present paper proposes an effective opportunistic grouping policy for multi-component multi-machine system considering time-based imperfect PM actions. The imperfect PM addresses the most practical issue that PM does not always return the component to as-good-as-new status. To the best of our knowledge, this is the first attempt to develop the multi-machine OM policy with multi-components. The objective is to obtain an optimum group of components and PM times in order to minimize the total system maintenance cost per unit time during the mission. The opportunistic grouping model is based on the individual component’s PM intervals. Two grouping strategies viz. grouping within the machines and grouping between the machines are adopted in order to identify the diversity of the proposed model. A recently developed meta-heuristic named Jaya algorithm is applied to optimize the objective function. The effectiveness of the proposed model is analyzed with an illustrative example. Results reveal that the proposed model shows better economic performance as compared from the individual maintenance practices. © 2018, Curran Associates Inc. All rights reserved.

Proceedings of International Conference on Computers and Industrial Engineering, CIE

Opportunistic group maintenance policy for multi-machine system with multi-components

It is mandatory to keep the total harmonic distortion in the output of most inverters below the limits prescribed by different international standards. The harmonic distortions caused due to nonlinear loads may not get corrected by typical magnitude controller, like PID controller. Repetitive controller is more effective in such situations. Often, repetitive controller is used as add-on block to the conventional magnitude controller. Design of repetitive controller can be easily implemented on digital platform. Rapid change in phase and magnitude of inverter-filter's transfer function near corner frequency causes instability problems in repetitive controller. Various techniques have been proposed by researchers to overcome this problem. Most of the reported techniques rely on digital compensation. However, it is hard to find a digital compensator, which simultaneously meets the phase and gain requirements at moderate computational effort. Here, a new output voltage feedback scheme has been proposed, which simplifies the requirement of digital compensation. The proposed scheme requires an extra hardware but at negligible added cost. In spite of this extra hardware, the proposed circuit turns out to be more energy efficient in comparison to few popular schemes, reported in literature, where some resistance is introduced in the inverter's filter for better stability of controller. In addition to the proposed modification the paper presents a simplified explanation of the various factors affecting stability of repetitive controller. The paper also discusses a novel experimental method for verifying the efficacy of repetitive controller in suppressing distortion of any particular harmonic order. © 1986-2012 IEEE.

IEEE Transactions on Power Electronics

A Modified Feedback Scheme Suitable for Repetitive Control of Inverter with Nonlinear Load

Two commercial diatomaceous earths were used as supports for the preparation of Mn/Co binary metal catalysts at different metal loads (5 to 10 wt \% Mn and 5 to 15 wt \% Co) by incipient wetness deposition. The activity of the prepared catalysts towards the complete oxidation of benzene to CO2 and water was investigated between 100 and 400◦ C. Raw supports and synthesized catalysts were characterized by XRD, N2 physisorption, SEM-EDS, H2 -TPR, and TPD. The purification treatment of food-grade diatomite significantly affected the crystallinity of this support while reducing its specific surface area (SSA). A loss of SSA, associated with the increase in the metal load, was observed on samples prepared on natural diatomite, while the opposite trend occurred with food-grade diatomite-supported catalysts. Metal nanoparticles of around 50 nm diameter were observed on the catalysts’ surface by SEM analysis. EDS analysis confirmed the uniform deposition of the active phases on the support’s surface. A larger H2 consumption was found by TPR analysis of natural diatomite-based samples in comparison to those prepared at the same metal load on food-grade diatomite. During the catalytic oxidation experiment, over 90\% conversion of benzene were achieved at a reaction temperature of 225◦ C by all of the prepared samples. In addition, the formation of coke during the oxidation tests was demonstrated by TGA analysis and the soluble fraction of the produced coke was characterized by GC-MS. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.

World University root node

Civil Engineering

Fulltext

Catalysts

A comparative study of Mn/Co binary metal catalysts supported on two commercial diatomaceous earths for oxidation of benzene

In present research paper, semi-transparent photovoltaic module (SPVM) integrated greenhouse solar drying system has been used for grapes (Vitis vinifera) drying. Based on hourly experimental information namely solar intensity, moisture evaporated, ambient air temperature, grape surface temperatures, relative humidity and greenhouse air temperature etc. heat and mass transfer coefficient for the SPVM drying system have been evaluated. It has been seen that the convective heat transfer coefficients for grapes found between 3.1–0.84 W/m2 K. Also, there is a fair agreement between theoretical and practical mass transfer (moisture evaporated) during drying of grapes with a correlation coefficient (r) and root mean square percentage deviation (e) of 0.88 and 11.56 respectively. Further, nonlinear regression procedure has been used to fit various drying models namely Henderson and Pabis model, Newton’s model, and Page’s model. From the analysis, it was found that Page’s model is best fitted for grapes drying in SPV greenhouse as well as open sun drying. Further, net electrical energy, thermal energy and equivalent thermal energy were found to be 3.61, 17.66 and 27.15 kWh during six days of drying respectively. © 2017, Springer-Verlag GmbH Germany, part of Springer Nature.

Heat and Mass Transfer/Waerme- und Stoffuebertragung

Grapes (Vitis vinifera) drying by semitransparent photovoltaic module (SPVM) integrated solar dryer: an experimental study

The presence of haze within the atmospheric medium degrades the quality of videos captured by camera sensors. The expulsion of haze, referred to as dehazing, is typically performed subject to the physical degradation display, that involves an explanation of an ill-posed inverse drawback. A few efforts have been made for image dehazing, whereas, video dehazing still remains an unexplored area of research. This paper proposes an approach for video dehazing combining the concepts of single image dehazing, optical stream estimation and Markov Random Field (MRF). The proposed method enhances the temporal and spatial coherence of the hazy video. Assuming that the dark channel of the haze-free picture is zero, we acquire the raw transmission map. In the proposed approach, we focus on the raw transmission map obtained from the dark channel prior using guided filter. We assess the forward and reverse optical streams between the neighboring frames to locate individual pixels using Linear Discriminant Analysis. The color of the haze-free pixels in the frames is approximated by a few hundred discrete colors, which generate a fixed cluster in space and the directions of the pixel. The pixels at a given cluster are spread and can be determined by analyzing the forward and in reverse optical frames to predict its value after haze removal. Largest Margin Nearest Neighbor (LMNN) algorithm is applied to get the smooth transmission map of the foggy frames of the video to approximate the pixel value in the RGB space. The stream fields are utilized in an augmented MRF model on the transmission guide obtained to enhance the temporal and the spatial coherence of the transmission. The proposed method is compared against the state-of-the-art on both real and synthetic videos to preserve the information optimally. © 2018 ACM.

Computer Science and Engineering

ACM International Conference Proceeding Series

Video Dehazing using LMNN with respect to Augmented MRF

In this paper we present a novel methodology for recognizing human activity in Egocentric video based on the Bag of Visual Features. The proposed technique is based on the assumption that, only a portion of the whole video can be sufficient to identify an activity. Rather, we argue that, for activity recognition in egocentric videos, the proposed approach performs better than any deep learning based method. Because, in egocentric videos, often the person wiring the sensor, becomes static for long time, or moves his head frequently. In both the cases, it becomes difficult to learn the spatiotemporal pattern of the video during action. The proposed approach divides the video into smaller video segments called Video Units. Spatio-temporal features extracted from the units, are clustered to construct the dictionary of Action Units (AU). The AUs are ranked based upon their score of likeliness. The scores are obtained by constructing a weighted graph with the AUs as vertices and edge weights calculated based on the frequencies of occurrences of the AUs during the activity. The less significant AUs are pruned out from the dictionary, and the revised dictionary of key AUs are used for activity classification. We test our approach on benchmark egocentric dataset and achieve a good accuracy. © 2018 ACM.

Activity Recognition in Egocentric Videos Using Bag of Key Action Units

Turmeric oil was extracted from Curcuma Longa herb (turmeric root) using supercritical fluid extraction (SFE) process. Full-face central composite design was employed to optimize operating parameters of the process. These parameters were pressure, temperature, solvent flow rate, particle size and addition of co-solvent (ethanol) that varied as 20–40 MPa, 40–60 °C, 5–15 g/min, 0–0.8 mm and 0–15% of solvent rate, respectively. Turmeric oil yield found through Soxhlet extraction was 5.954 wt% of turmeric powder whereas through SFE, it varied from 2 to 5.3 wt%. Turmerone and curcumin were identified as principle compounds of turmeric essential oil, which were analyzed using Gas chromatography–mass spectrometry and Ultraviolet–visible Spectrophotometer, respectively. Experimental data of oil yield, Curcumin content and Turmerone content were fitted well in the Quadratic model. Optimized values of operating parameters for maximizing these responses were also predicted. Further, economic assessment of SFE of turmeric oil at industrial scale for 60 t/y production capacity was performed. © 2018 Elsevier Ltd

Chemical Engineering

Journal of Cleaner Production

Influence of operating parameters on supercritical fluid extraction of essential oil from turmeric root

Luminescent trivalent europium(III) complexes Eu(CHPB)3·(H2O)2 (C1), Eu(CHPB)3·neo (C2), Eu(CHPB)3·batho (C3), Eu(CHPB)3·phen (C4) and Eu(CHPB)3·bipy (C5) have been synthesized by involving a β-diketone ligand 1-(5-chloro-2-hydroxyphenyl)-1,3-butanedione (CHPB) and four ancillary ligands like neocuproine (neo), bathophenanthroline (batho), 1,10-phenanthroline (phen) and 2,2-bipyridyl (bipy). All the synthesized complexes C1–C5 were investigated by adopting various techniques such as elemental (CHN) analysis, 1H NMR spectroscopy, IR spectroscopy, UV–visible, thermal analysis (TG/DTG) and photoluminescence (PL) spectroscopy. The luminescence of complexes C1–C5 gets intensified suggesting a favorable position of triplet state of ligand and coligand from the emitting levels of metal ion. The luminescence quantum efficiencies and Judd-Ofelt intensity parameter Ω2 of the complexes also determined which advocate higher polarizable ligand field around central metal ion. © 2017 Elsevier B.V.

Inorganica Chimica Acta

Judd-Ofelt characterization and energy transfer mechanism of highly luminescent europium(III) complexes with 1-(5-chloro-2-hydroxyphenyl)-1,3-butanedione