Browsing by Author "Roy, S."

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A Comprehensive Review on the Use of Wastewater in the Manufacturing of Concrete: Fostering Sustainability through Recycling
(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Maddikeari, M.; Das, B.B.; Tangadagi, R.B.; Roy, S.; Priyanka, P.B.; Ramachandra, M.L.
The primary aim of this review article is to find the influence of wastewater and its characteristics on recycling as an alternative to potable water for concrete preparation. On the other hand, scarcity, and the demand for freshwater for drinking are also increasing day by day around the globe. About a billion tons of freshwater is consumed daily for concrete preparation for various operations such as mixing and curing, to name a few. The rapid development of certain industries such as textile, casting, stone cutting, and concrete production has caused the water supply to be severely affected. Recycling wastewater in concrete offers various potential benefits like resource conservation, environmental protection, cost savings, and enhanced sustainability. This article reviews the effect of various types of wastewater on various physical and chemical properties of wastewater, rheological characteristics, strength, durability, and microstructure properties of concrete. It also explores the potential effects of decomposing agents on enhancing concrete properties. Currently, limited research is available on the use of various types of wastewater in concrete. Hence, there is a need to develop various methods and procedures to ensure that the utilization of wastewater and treated wastewater is carried out in the production of concrete in a sustainable manner. Although wastewater can reduce the workability of fresh concrete, it can also increase its strength and long-term performance of concrete. The use of various types of wastewater, such as reclaimed water and tertiary-treated wastewater, was found to be superior compared to those using industrial- or secondary-treated wastewater. Researchers around the globe agree that wastewater can cause various detrimental effects on the mechanical and physical properties of concrete, but the reductions were not significant. To overcome limited scientific contributions, this article reviews all the available methods of using various types of wastewater to make concrete economically and environmentally friendly. This research also addresses possible challenges with respect to the demand for freshwater and the water crisis. © 2024 by the authors.
A Decentralized Nonlinear Control Scheme for Modular Power Sharing in DC-DC Converters
(Institute of Electrical and Electronics Engineers Inc., 2021) Roy, S.; Joisher, M.; Hanson, A.J.
Modular power conversion systems can have a variety of potential advantages, including high thermal contact area, reliability, repairability, wide operating range, the use of devices with reduced voltage and/or current ratings and better Figure of merit, and overall small parasitics to enable high-frequency operation even at high power. In order to ensure power sharing among modules, most approaches adopt a centralized or distributed approach which require communication with a central controller or among modules, which increases the opportunity for global system failure and impedes modularity. In this paper, we present a truly decentralized control approach (one with no communication between modules) for power sharing in modular converters. Each module's controller implements a nonlinear 'selfish' control algorithm, wherein the increment or decrement in its power at any time instant is a function of its present contribution to the overall output power. That is, modules currently processing high power respond strongly when less power is required, but weakly when more power is required (and vice versa for modules currently processing low power). The successful operation of the proposed control strategy is first verified using simulation results which show its fast convergence and stable operation in IPOP, ISOP, IPOS and ISOS configurations without changing any physical or control parameters. Further validation is presented through the successful operation of a hardware prototype when arranged in different modular configurations, as well as its stable operation over load transients and in the event of module failure. Â© 2021 IEEE.
A Low Mismatch Current Steering Charge Pump forÂ High-Speed PLL
(Springer Science and Business Media Deutschland GmbH, 2023) Roy, S.; Lad, K.H.; Rekha, S.; Laxminidhi, T.
This paper presents the design of a charge pump based on the current steering and positive feedback topology to support application in high-speed PLLs. The primary objective of the design is to counter current mismatch in charging and discharging currents as well as maintain fast operation with the help of positive feedback assisted current steering topology. This charge pump is designed in UMC 65nm CMOS technology and its functionality, characteristics and amount of current mismatch are verified across voltage and temperature variations. Â© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
A study about color normalization methods for histopathology images
(Elsevier Ltd, 2018) Roy, S.; Kumar Jain, A.K.; Lal, S.; Kini, J.R.
Histopathology images are used for the diagnosis of the cancerous disease by the examination of tissue with the help of Whole Slide Imaging (WSI) scanner. A decision support system works well by the analysis of the histopathology images but a lot of problems arise in its decision. Color variation in the histopathology images is occurring due to use of the different scanner, use of various equipments, different stain coloring and reactivity from a different manufacturer. In this paper, detailed study and performance evaluation of color normalization methods on histopathology image datasets are presented. Color normalization of the source image by transferring the mean color of the target image in the source image and also to separate stain present in the source image. Stain separation and color normalization of the histopathology images can be helped for both pathology and computerized decision support system. Quality performances of different color normalization methods are evaluated and compared in terms of quaternion structure similarity index matrix (QSSIM), structure similarity index matrix (SSIM) and Pearson correlation coefficient (PCC) on various histopathology image datasets. Our experimental analysis suggests that structure-preserving color normalization (SPCN) provides better qualitatively and qualitatively results in comparison to the all the presented methods for breast and colorectal cancer histopathology image datasets. © 2018 Elsevier Ltd
A Survey ofÂ Hyperparameter Selection Methods forÂ Weather Forecasting Using State-of-the-Art Machine Learning Algorithms
(Springer Science and Business Media Deutschland GmbH, 2025) Sen, A.; Sen, U.; Paul, M.; Sutradhar, A.; Vankala, T.N.; Mallick, C.; Mallik, A.; Roy, A.; Sai, S.; Roy, S.
Weather forecasting is an important aspect across various sectors, but the intricate dynamics of weather systems pose a challenge for conventional statistical models to forecast accurately. Besides auto-regressive time forecasting models like ARIMA, deep learning architectures like ANNs, LSTMs, and GRU networks have been shown to enhance the accuracy of forecasts by considering temporal dependencies. This paper studies various machine learning models like XGBoost, SVR, KNN Regressor, Random Forest Regressor and the application of metaheuristic algorithms, like Genetic Algorithm (GA), Differential Evolution (DE), and Particle Swarm Optimization (PSO), on some deep learning model architectures like ANNs, LSTMs and GRUs, to automate the process of finding the best hyperparameters for the models. Furthermore, this paper explores the Quantum LSTM (QLSTM) network and novel QLSTM Ensemble models. We conduct a comparative study of these model structures, evaluating their effectiveness in weather prediction using measures such as Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). The findings underscore the capabilities of metaheuristic algorithms and innovative quantum methods in enhancing the precision of weather forecasts. Â© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
All that Glitters Is Not Gold: A Probe into Photocatalytic Nitrate Reduction Mechanism over Noble Metal Doped and Undoped TiO2
(2017) Challagulla, S.; Tarafder, K.; Ganesan, R.; Roy, S.
Photocatalytic reduction of aqueous nitrate has been thoroughly studied over noble metals doped and pristine TiO2 synthesized by a customized single step microwave assisted hydrothermal method. The synthesized catalysts are systematically characterized using XRD, Raman spectroscopy, FE-SEM, HR-TEM, XPS, diffuse reflectance spectroscopy, and PL measurements. The characterization reveals the successful synthesis of highly crystalline doped and undoped nano-TiO2. The photocatalytic rate of aqueous nitrate reduction over undoped TiO2 is found to be higher than that of noble metal doped TiO2. Mechanistic studies of the photocatalytic reduction are carried out with the help of different hole (oxalic acid, and methanol) and electron (sodium persulfate) scavengers, which reveal that the photogenerated electrons are the primary agents toward efficient nitrate photoreduction. Detailed studies have revealed that the noble metal doping in TiO2 helps in efficient photogeneration of H2 compared to the undoped analogue, however, the in situ produced H2 is found to be inefficient in reducing NO3-. The conduction band position from first principle calculations with respect to the nitrate and hydrogen reduction potentials derived from cyclic voltammetry provide insights to the electron transfer process in determining the reaction pathway. 2017 American Chemical Society.
All that Glitters Is Not Gold: A Probe into Photocatalytic Nitrate Reduction Mechanism over Noble Metal Doped and Undoped TiO2
(American Chemical Society service@acs.org, 2017) Challagulla, S.; Tarafder, K.; Ganesan, R.; Roy, S.
Photocatalytic reduction of aqueous nitrate has been thoroughly studied over noble metals doped and pristine TiO2 synthesized by a customized single step microwave assisted hydrothermal method. The synthesized catalysts are systematically characterized using XRD, Raman spectroscopy, FE-SEM, HR-TEM, XPS, diffuse reflectance spectroscopy, and PL measurements. The characterization reveals the successful synthesis of highly crystalline doped and undoped nano-TiO2. The photocatalytic rate of aqueous nitrate reduction over undoped TiO2 is found to be higher than that of noble metal doped TiO2. Mechanistic studies of the photocatalytic reduction are carried out with the help of different hole (oxalic acid, and methanol) and electron (sodium persulfate) scavengers, which reveal that the photogenerated electrons are the primary agents toward efficient nitrate photoreduction. Detailed studies have revealed that the noble metal doping in TiO2 helps in efficient photogeneration of H2 compared to the undoped analogue, however, the in situ produced H2 is found to be inefficient in reducing NO3-. The conduction band position from first principle calculations with respect to the nitrate and hydrogen reduction potentials derived from cyclic voltammetry provide insights to the electron transfer process in determining the reaction pathway. © 2017 American Chemical Society.
Influence of mixed convection in an exponentially decreasing external flow velocity
(2017) Patil, P.M.; Ramane, H.S.; Roy, S.; Hindasageri, V.; Momoniat, E.
This article explores the influence of mixed convection in a steady incompressible laminar boundary layer flow for an exponentially decreasing free stream velocity in presence of surface mass transfer and heat source or sink. The nonlinear partial differential equations governing the flow and thermal fields are expressed in dimensionless form with the help of suitable non-similar transformations. The mathematical complexities in obtaining non-similar solutions at the leading edge of the streamwise coordinate as well as non-similarity variable ? have overcome by using the implicit finite difference scheme in conjunction with Quasi-linearization technique by choosing an appropriate finer step sizes along the streamwise direction. The effects of various dimensionless physical parameters on velocity and thermal fields are analysed. 2016 Elsevier Ltd
Influence of mixed convection in an exponentially decreasing external flow velocity
(Elsevier Ltd, 2017) Patil, P.M.; Ramane, H.S.; Roy, S.; Hindasageri, V.; Momoniat, E.
This article explores the influence of mixed convection in a steady incompressible laminar boundary layer flow for an exponentially decreasing free stream velocity in presence of surface mass transfer and heat source or sink. The nonlinear partial differential equations governing the flow and thermal fields are expressed in dimensionless form with the help of suitable non-similar transformations. The mathematical complexities in obtaining non-similar solutions at the leading edge of the streamwise coordinate as well as non-similarity variable ? have overcome by using the implicit finite difference scheme in conjunction with Quasi-linearization technique by choosing an appropriate finer step sizes along the streamwise direction. The effects of various dimensionless physical parameters on velocity and thermal fields are analysed. © 2016 Elsevier Ltd
Mechanistic insight and first principle analysis of cation-inverted zinc ferrite nanostructure: A paradigm for ppb-level room temperature NOx sensor
(Elsevier B.V., 2024) Nath, V.G.; Ray, S.; Rodney, J.D.; Prakasha Bharath, S.; Roy, S.; Tarafder, K.; Subramanian, A.; Chul Kim, B.
Herein, we adopted a new paradigm for developing a high-performance gas sensor by leveraging the mixed spinel ZnFe2O4 structure (mZFO) to enhance the adsorption of NOx molecules. Material characterization reveals the formation of the mZFO due to the cation inversion in lattice sites. The estimated value of the inversion degree is observed to shift from 0.78 to 0.39 with an increase in the calcination temperature. The mZFO nanoparticles calcined at 500 °C show exceptional sensing performance due to their suitable grain size (∼2 times Debye length), neck diameter, and surface area. The sensing studies conducted at various NOx concentrations indicate that the sensor can detect ppb level of NOx with a detection limit of about 9 ppb at room temperature. The detailed sensing mechanism is elucidated based on the density functional theory calculations (DFT) and Bader charge analysis. The outstanding sensor performance is attributed to the formation of a mixed spinel structure, wherein the adsorption energy of NOx (∼-0.6 eV) in the presence of surface adsorbed oxygen is higher than that of the normal spinel structure (∼-0.1 eV). Furthermore, the sensor exhibited a fast response and recovery times (7 and 92 s at 800 ppb NO2), excellent stability, and selectivity. The practical suitability of the mZFO sensor was studied by analyzing the vehicle exhaust emissions. We strongly believe this work would pave a novel approach to developing a high-potential gas sensor by modifying the cation distributions in the spinel ferrites. © 2024 Elsevier B.V.
Novel color normalization method for hematoxylin eosin stained histopathology images
(2019) Roy, S.; Lal, S.; Kini, J.R.
With the advent of computer-assisted diagnosis (CAD), the accuracy of cancer detection from histopathology images is significantly increased. However, color variation in the CAD system is inevitable due to the variability of stain concentration and manual tissue sectioning. The small variation in color may lead to the misclassification of cancer cells. Therefore, color normalization is a very much essential step prior to segmentation and classification in order to reduce the inter-variability of background color among a set of source images. In this paper, a novel color normalization method is proposed for Hematoxylin and Eosin stained histopathology images. Conventional Reinhard algorithm is modified in our proposed method by incorporating fuzzy logic. Moreover, mathematically, it is proved that our proposed method satisfies all three hypotheses of color normalization. Furthermore, several quality metrics are estimated locally for evaluating the performance of various color normalization methods. The experimental result reveals that our proposed method has outperformed all other benchmark methods. 2019 IEEE.
Novel color normalization method for hematoxylin eosin stained histopathology images
(Institute of Electrical and Electronics Engineers Inc., 2019) Roy, S.; Lal, S.; Kini, J.R.
With the advent of computer-assisted diagnosis (CAD), the accuracy of cancer detection from histopathology images is significantly increased. However, color variation in the CAD system is inevitable due to the variability of stain concentration and manual tissue sectioning. The small variation in color may lead to the misclassification of cancer cells. Therefore, color normalization is a very much essential step prior to segmentation and classification in order to reduce the inter-variability of background color among a set of source images. In this paper, a novel color normalization method is proposed for Hematoxylin and Eosin stained histopathology images. Conventional Reinhard algorithm is modified in our proposed method by incorporating fuzzy logic. Moreover, mathematically, it is proved that our proposed method satisfies all three hypotheses of color normalization. Furthermore, several quality metrics are estimated locally for evaluating the performance of various color normalization methods. The experimental result reveals that our proposed method has outperformed all other benchmark methods. © 2019 IEEE.
Novel edge detection method for nuclei segmentation of liver cancer histopathology images
(Springer Science and Business Media Deutschland GmbH, 2023) Roy, S.; Das, D.; Lal, S.; Kini, J.
In automatic cancer detection, nuclei segmentation is a very essential step which enables the classification task simpler and computationally more efficient. However, automatic nuclei detection is fraught with the problems of inter-class variability of nuclei size and shapes. In this research article, a novel unsupervised edge detection technique, is proposed for segmenting the nuclei regions in liver cancer Hematoxylin and Eosin (H&E) stained histopathology images. In this novel edge detection technique, the notion of computing local standard deviation is incorporated, instead of computing gradients. Since, local standard deviation value is correlated with the edge information of image, this novel method can extract the nuclei edges efficiently, even at multiscale. The edge-detected image is further converted into a binary image by employing Ostu (IEEE Trans Syst Man Cybern 9(1):62–66, 1979)’s thresholding operation. Subsequently, an adaptive morphological filter is also employed in order to refine the final segmented image. The proposed nuclei segmentation method is also tested on a well-recognized multi-organ dataset, in order to check its effectiveness over wide variety of dataset. The visual results of both datasets indicate that the proposed segmentation method overcomes the limitations of existing unsupervised methods, moreover, its performance is comparable with the same of recent deep neural models like DIST, HoverNet, etc. Furthermore, three quality metrics are computed in order to measure the performance of several nuclei segmentation methods quantitatively. The mean value of quality metrics reveals that proposed segmentation method indeed outperformed other existing nuclei segmentation methods. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Photo- and Electrocatalytic Reduction of CO2 over Metal-Organic Frameworks and Their Derived Oxides: A Correlation of the Reaction Mechanism with the Electronic Structure
(American Chemical Society, 2022) Payra, S.; Ray, S.; Sharma, R.; Tarafder, K.; Mohanty, P.; Roy, S.
A Ce/Ti-based bimetallic 2-aminoterephthalate metal-organic framework (MOF) was synthesized and evaluated for photocatalytic reduction of CO2 in comparison with an isoreticular pristine monometallic Ce-terephthalate MOF. Owing to highly selective CO2 adsorption capability, optimized band gaps, higher flux of photogenerated electron-hole pairs, and a lower rate of recombination, this material exhibited better photocatalytic reduction of CO2 and lower hydrogen evolution compared to Ce-terephthalate. Thorough probing of the surface and electronic structure inferred that the reducibility of Ce4+ to Ce3+ was due to the introduction of an amine functional group into the linker, and low-lying Ti(3d) orbitals in Ce/Ti-2-aminoterephthalate facilitated the photoreduction reaction. Both the MOFs were calcined to their respective oxides of Ce1-xTixO2 and CeO2, and the electrocatalytic reduction of CO2 was performed over the oxidic materials. In contrast to the photocatalytic reaction mechanism, the lattice substitution of Ti in the CeO2 fluorite cubic structure showed a better hydrogen evolution reaction and consequently, poorer electroreduction of CO2 compared to pristine CeO2. Density functional theory calculations of the competitive hydrogen evolution reaction on the MOF and the oxide surfaces corroborated the experimental findings. © 2022 American Chemical Society.
QGAPHnet : Quantum Genetic Algorithm Based Hybrid QLSTM Model for Soil Moisture Estimation
(Institute of Electrical and Electronics Engineers Inc., 2024) Sai, S.; Sen, A.; Mallick, C.; Mallik, A.; Sen, U.; Paul, M.; Sutradhar, A.; Roy, S.
Soil moisture, pH, soil temperature, humidity among other factors play a pivotal role in affecting the agricultural productivity of a region, influencing factors such as crop yield, organic carbon estimation, and crop growth analysis. This paper introduces a comprehensive investigation into soil moisture and temperature dynamics, employing a dynamic soil moisture dataset. Utilising Quantum Long Short Term Memory (QLSTM), we apply Quantum Genetic Algorithm (QGA) and Particle Swarm Optimisation (PSO) to study and predict patterns within the dataset. Our approach not only enhances the precision of soil moisture estimations but also provides a novel perspective on environmental factors. The findings from this study hold significant implications for understanding and managing soil moisture in diverse contexts, spanning agriculture, hydrology, and ecosystem studies. Â© 2024 IEEE.
Quantum Machine Learning: A Review and Current Status
(Springer Science and Business Media Deutschland GmbH, 2021) Mishra, N.; Kapil, M.; Rakesh, H.; Anand, A.; Mishra, N.; Warke, A.; Sarkar, S.; Dutta, S.; Gupta, S.; Prasad Dash, A.; Gharat, R.; Chatterjee, Y.; Roy, S.; Raj, S.; Kumar Jain, V.; Bagaria, S.; Chaudhary, S.; Singh, V.; Maji, R.; Dalei, P.; Behera, B.K.; Mukhopadhyay, S.; Panigrahi, P.K.
Quantum machine learning is at the intersection of two of the most sought after research areasâ€”quantum computing and classical machine learning. Quantum machine learning investigates how results from the quantum world can be used to solve problems from machine learning. The amount of data needed to reliably train a classical computation model is evergrowing and reaching the limits which normal computing devices can handle. In such a scenario, quantum computation can aid in continuing training with huge data. Quantum machine learning looks to devise learning algorithms faster than their classical counterparts. Classical machine learning is about trying to find patterns in data and using those patterns to predict further events. Quantum systems, on the other hand, produce atypical patterns which are not producible by classical systems, thereby postulating that quantum computers may overtake classical computers on machine learning tasks. Here, we review the previous literature on quantum machine learning and provide the current status of it. Â© 2021, Springer Nature Singapore Pte Ltd.
Rhodamine-based Cu2+-selective fluorosensor: Synthesis, mechanism, and application in living cells
(2013) Sikdar, A.; Roy, S.; Haldar, K.; Sarkar, S.; Panja, S.S.
A rhodamine B-based fluorescence probe (1) for the sensitive and selective detection of Cu2+ ion has been designed and synthesized using pyridine moiety. The optical properties of this compound have been investigated in acetonitrile-water binary solution (7:3 v/v). Compound 1 is found to be an excellent sensor for a biologically/physiologically very important transition metal ion (Cu2+) using only the two very different modes of measurements (absorption and emission)
Rhodamine-based Cu2+-selective fluorosensor: Synthesis, mechanism, and application in living cells
(2013) Sikdar, A.; Roy, S.; Haldar, K.; Sarkar, S.; Panja, S.S.
A rhodamine B-based fluorescence probe (1) for the sensitive and selective detection of Cu2+ ion has been designed and synthesized using pyridine moiety. The optical properties of this compound have been investigated in acetonitrile-water binary solution (7:3 v/v). Compound 1 is found to be an excellent sensor for a biologically/physiologically very important transition metal ion (Cu2+) using only the two very different modes of measurements (absorption and emission); one case displayed intensity enhancement whereas in other case showed intensity depletion (quenching). A mechanistic investigation has been performed to explore the static nature of quenching process. The sensor has been found to be very effective in sensing Cu 2+ ion inside living cells also. © 2013 Springer Science+Business Media New York.
The structural and surface modification of zeolitic imidazolate frameworks towards reduction of encapsulated CO2
(2018) Payra, S.; Challagulla, S.; Indukuru, R.R.; Chakraborty, C.; Tarafder, K.; Ghosh, B.; Roy, S.
ZIF-8, a metal organic framework with a sodalite topological structure, is a widely studied crystalline microporous material due to its thermal and chemical stability. However, the existing studies mostly focus on understanding the porosity and bulk structure of ZIF-8, ignoring the external facets of the porous crystal, which are the first points of interaction between adsorbent and guest adsorbate. This paper reports on understanding the preferential exposure of thermodynamically stable and unstable facets as a function of synthetic methodology. The comprehensive and combinatorial investigation of experimental and theoretical studies shows that the high energy {112} facets of ZIF-8 efficiently reduce the encapsulated CO2 to fuel compared to the {011} facets. The Royal Society of Chemistry and the Centre National de la Recherche Scientifique.
Structure sensitive photocatalytic reduction of nitroarenes over TiO2
(2017) Challagulla, S.; Tarafder, K.; Ganesan, R.; Roy, S.
It is a subject of exploration whether the phase pure anatase or rutile TiO2 or the band alignment due to the heterojunctions in the two polymorphs of TiO2 plays the determining role in efficacy of a photocatalytic reaction. In this work, the phase pure anatase and rutile TiO2 have been explored for photocatalytic nitroarenes reduction to understand the role of surface structures and band alignment towards the reduction mechanism. The conduction band of synthesized anatase TiO2 has been found to be more populated with electrons of higher energy than that of synthesized rutile. This has given the anatase an edge towards photocatalytic reduction of nitroarenes over rutile TiO2. The other factors like adsorption of the reactants and the proton generation did not play any decisive role in catalytic efficacy. 2017 The Author(s).