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Synergistic effect of bio-nanocarbon embedded polymer nanocomposite and its applications
For applications involving sustainable materials, bio-nanocarbon was examined as a material to improve the properties of fiber-reinforced nanobiocomposite. A thorough investigation has been conducted using nano biocarbon as a filler and reinforcing material. However, the composite's inferior mechanical, physical, and thermal properties are a result of a poor fiber-matrix interface. As a result, in this study, biocarbon nanoparticles were created and used as functional components to enhance the properties of polymeric composite materials. To emphasize the scientific and technological issues that need to be resolved in order to create artificial composites with bio-inspired structures, recent studies of bio-inspired nano-carbon composites are discussed in this study. These include the production techniques for resolving the nanocarbon dispersion problem and creating bio-inspired structures, as well as the microstructure and composite characteristics characterization. In order to reveal natural design principles and serve as a resource for future research, bio-inspired composites and their applications are thoroughly examined and explained. 2023 Bentham Science Publishers. -
Synergistic Co-grafting of multiwalled carbon nanotubes using SO3H and choline chloride-urea in fabricating uniform thin films with enhanced visible light transparency and reduced sheet resistance
New materials and innovative modification methods are indispensable to advance the energy field. The present work reports the fabrication of transparent conducting electrodes using Multiwalled carbon nanotube (MWCNT) that have been modified with sulfonic acid (SO3H) and a combination of Choline Chloride-Urea/Sulfonic acid (DES/SO3H). A comprehensive investigation was conducted to ascertain the impact of employing DES and SO3H in achieving consistent and long-lasting dispersions of multiwalled carbon nanotubes in different solvents and the most favourable condition was achieved when employing n-heptanol. The films were fabricated on glass substrate by using the spray pyrolysis technique. The stability of the system following the modification was unequivocally confirmed by SEM analysis, while the electronic structure was assessed qualitatively by EDX analysis. Optical profilometry analysis revealed that the film thickness fell within the range of 350385 nm. The co-grafted film demonstrated an optical transparency of approximately 84.96%, modestly exceeding that of the singly grafted film, which was determined to be 70.14% in the visible region. The sheet resistance of DES/S-MWCNT and S-MWCNTs was calculated to be approximately 3.33k?/Sq and 5.02k?/Sq, respectively. The calculated charge transfer resistance (RCT) for the co-grafted and singly grafted MWCNT systems was 0.185? and 0.190?, respectively. These values align closely with the corresponding sheet resistance values obtained. The electrochemical investigations also showed an increased specific capacity for DES/S-MWCNT, approximately 896.2C/g, whereas the calculated value for the S-MWCNT system was 826.8C/g. 2024 Elsevier B.V. -
Synergistic advancements in energy storage: g-C3N4/NiFe2O4/PANI composite with augmented electrochemical capabilities
This study examines the electrochemical behaviour of a hybrid composite material of graphitic carbon nitride/Nickel ferrite/Polyaniline (g-C3N4/NiFe2O4/PANI) synthesized by hydrothermal method, coupled with in-situ polymerisation. The ensuing g-C3N4/NiFe2O4/PANI composite demonstrates superior characteristics for energy storage applications. Through a comprehensive analysis, we elucidate the combined effects of the distinct components, revealing improved electrochemical properties. The composite exhibits improved galvanostatic charge/discharge exhibiting a specific capacitance of 770 Fg?1 at 1 Ag?1 current density. This research underscores the perspective of the g-C3N4/NiFe2O4/PANI composite as a promising candidate for advanced energy storage systems. 2024 Elsevier Ltd -
Synergetic effects of cross-linking and incorporation of Fe-Al bimetallic combination on the properties of polyvinyl alcohol novel films
Polyvinyl alcohol films incorporated with Fe-Al bimetallic combination novel films were synthesized by sol-gel method in the presence of glutaraldehyde (GA). The results of FTIR spectra confirmed the cross-linking between PVA and GA, resulted in the formation of rigid molecular chains. The comparison of thermograms of pure PVA and Fe-Al PVA films cured with GA indicated the enhanced thermal stability of the cured films. The electrical properties of the pure PVA films and bimetallic PVA films cured with GA were studied in the frequency range 100 Hz to 100 kHz. The current study explains the effect of GA and incorporation of Fe-Al bimetallic combination towards the structural modification and dielectric properties like dielectric constant, dielectric loss, ac conductivity, polarization, and permittivity of the cured PVA films. The variation of the storage modulus of cured PVA films as a function of temperature has also been studied. 2023, Qatar University and Springer Nature Switzerland AG. -
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Synergetic Effect of Metal Nanoparticle Embedded Graphene Membrane : A Novel Approach for Antimicrobial Filtration
Water, the elixir of life, holds a profound significance that extends far beyond its essential utility. It's not just a resource; it pulsates as the life force of our existence, intricately woven into the very fabric of our daily lives. Water is the silent force that shapes our world, from nurturing our health and sustaining social structures to fueling economic development and fostering the environment. However, the adequacy of potable water quality confronts adverse impacts stemming from inadequate wastewater treatment, escalating domestic and industrial waste, and the microbial contamination of surface water sources. Furthermore, climate change emerges as a pivotal factor intensifying the depletion of water levels in natural resources due to diminished rainfall. Reports project that, by 2025, two-thirds of global population might contend with water scarcity. Given the persistence of current scenario, there exists a notable potential for significant conflicts among nations stemming from water scarcity. However, such a predicament can be mitigated through proactive measures, including the preservation of natural resources and the implementation of advanced technologies to recover fresh water from contaminated sources. Advanced technologies for the purification of contaminated water encompass sedimentation, precipitation, filtration, and ion exchange, which can effectively extract clean water from diverse impurities. Notably, membrane-based purification has gained prominence in recent years, owing to its cost- effectiveness and energy-saving attributes. Carbon-based nanomaterials, including carbon nanotubes,fullerenes and graphene have garnered considerable attention in recent research studies, particularly in the realm of membrane applications. Within this, membranes fabricated by carbon nanotubes (CNT) stand out, showcasing exceptional filtering properties attributed to their tubular carbon structure. However, the cost-effectiveness and ease of synthesis impediments pose significant challenges, acting as bottlenecks for their widespread application in water purification. Consequently, graphene-based membranes emerge as a promising alternative to CNT membranes, demonstrating selective separation of ions and molecules. Specifically, membranes derived from graphene oxide (GO) and reduced graphene oxide (rGO) exhibit superior filtering capabilities compared to ceramic and polymeric counterparts, owing to their layered structure featuring tunable nanochannels, hydrophilic or hydrophobic nature, and commendable mechanical resilience. Graphene oxide solution synthesis has been done using Hummer's method, followed by fabrication of high-quality membranes through vacuum filtration techniques. Current work emphasis on recognizing the pivotal influence of membrane thickness on both water flux and dye rejection, meticulous optimization of filtration properties by producing graphene oxide (GO) membranes at various concentrations. Furthermore, reduction of graphene oxide through the hydrothermal method, enabling a comprehensive comparative analysis of water flux and rejection between graphene oxide (GO) and reduced graphene oxide (rGO) membranes was carried out. In our investigation, the results unequivocally validate that the GO 500 sample exhibits optimized filtration properties. Furthermore, the reduced graphene oxide (rGO) variant surpasses graphene oxide (GO) in terms of filtration efficacy, demonstrating superior filtering properties. It is noteworthy to highlight that reduced graphene oxide (rGO) exhibits less antibacterial properties compared to graphene oxide (GO). The disinfection capability of the membrane is pivotal in ensuring the recovery of pure water. To bolster the antibacterial features of GO, we have undertaken an enhancement strategy by incorporating silver nanoparticles. Silver nanoparticle, showcases multifaceted properties including surface plasmon resonance and unique morphologies, which contribute significantly to the inactivation of bacteria. The conducted studies reveal that membranes incorporating graphene oxide with silver (GO-Ag) exhibit remarkable antibacterial properties against both gram-positive and gram-negative bacteria. Additionally, these membranes demonstrate appreciable filtration capabilities and exhibit effective antifouling properties, further emphasizing their potential for advanced applications in water purification systems. Fouling is a significant challenge in membrane technology, as the continuous passage of contaminants results in the formation of layers on membrane surface, thereby diminishing its filtration efficiency. Despite the antifouling properties exhibited by GO- Ag membranes, there exists further improvement in enhancing performance and extending the membrane's lifespan. To address this, we have undertaken a reduction of graphene oxide and incorporated silver nanoparticles, aiming to augment the antifouling properties and overall efficacy of membrane. The conclusive findings indicate that fine-tuned membrane exhibits remarkable antibacterial properties, superior filtration capabilities, and a minimal irreversible fouling ratio. These outcomes provide confirmation that the fabricated membranes stand as potential materials for water purification applications, showcasing a well-rounded set of properties essential for effective and sustainable water treatment. -
Synchronous learning and asynchronous learning during COVID-19 pandemic: a case study in India
Purpose: This research aims to study the students' perspectives on synchronous and asynchronous learning during the COVID-19 Pandemic. Both synchronous and asynchronous learning approaches used in online education have positive and negative outcomes. Hence, the aim is to study online education's positive and negative consequences, reflecting sync and async approaches. This research followed a mixed research approach. The key stakeholders of this research are the Indian educational institutions and students. Design/methodology/approach: This research collected data from the students undergoing synchronous and asynchronous learning amidst the COVID-19 Pandemic. The data were collected (N=655) from various students taking online classes during the pandemic. A questionnaire survey was distributed to the students through online platforms to collect the data. In this research, the authors have collected data using simple random sampling, and the same has been used for data analysis using SPSS version 26. The collected data were exposed to a factor analysis using a principal component analysis technique to reduce the vast dimensions. Findings: The study findings show that synchronous learning is sometimes stressful, placing more responsibility on students mainly because of the increased screen time. At the same time, asynchronous learning allows the students to self-explore and research the topics assigned to them. Students also felt that asynchronous activities create a burden because of many written assignments to be submitted within a short period. Overall, the COVID-19 pandemic has been challenging for the students and the teachers. However, teachers have helped students to learn through digital platforms. The majority of the respondents opined that technological disruptions and death in the family circle had been significant reasons for not concentrating during online classes. However, the combination of synchronous and asynchronous learning has led to a balanced education. Practical implications: Higher education has undergone multiple transformations in a short period (from March 2020, 2021 and beyond). Educational institutions underwent a rapid transition in remote teaching and learning in the initial stages. As time progressed, educational institutions did course navigation where they relooked into their course plans, syllabus and brought a structural change to match the pandemic requirements. Meanwhile, educational institutions slowly equipped themselves with infrastructure facilities to bring academic integrity. At present, educational institutions are ready to face the new normality without disrupting services to society. Social implications: Educational institutions create intellectual capital, which is important for the development of the economy. In the light of COVID-19, there are new methods and approaches newly introduced or old methods and approaches, which are reimplemented, and these approaches always work for the benefit of the student community. Originality/value: The authors collected data during the COVID-19 pandemic; it helped capture the students' experience about synchronous and asynchronous learning. Students and faculty members are newly exposed to synchronous and asynchronous learning, and hence, it is essential to determine the outcome that will help many stakeholders. 2022, Cassandra Jane Fernandez, Rachana Ramesh and Anand Shankar Raja Manivannan. -
Symmetric Supercapacitors based on Reduced Graphene Oxide/Multi-walled Carbon Nanotubes/Cobalt Oxide Ternary Composites
Ternary nanocomposites of reduced graphene oxide/multi-walled carbon nanotubes/cobalt oxide nanoparticles (rGO/MWCNT/Co3O4) were synthesized employing a facile hydrolysis method with subsequent heat treatment. The good electrical conductivity and remarkable carrier mobility of rGO and MWCNTs make them a suitable matrix for hybrid supercapacitors, and their composites with metal oxides exhibit enhanced electrochemical properties due to the advantages of the synergistic contribution and the integration of different dimensionalities. The binary counterparts of Co3O4 with GO or MWCNTs were also produced using the same technique to gain additional insight into the characteristics of the individual components. The structural and morphological properties of the composites were analyzed using various analytical techniques. The electrochemical behaviors of the prepared composites were investigated using cyclic voltammetry (CV), galvanostatic chargedischarge (GCD), and electrochemical impedance spectroscopy (EIS) in 1 M H2SO4. A platinum electrode modified with the rGO/MWCNT/Co3O4 composite displayed a remarkable specific capacitance of 922 F g?1 at a current density of 1 A g?1 composite with a negligible capacitance drop after 2000 cycles. The symmetric supercapacitor fabricated using the rGO/MWCNT/Co3O4 composite showed an energy density of 32.2 Wh Kg?1 at 1 A g?1, and the corresponding power density was 2000 W Kg?1. The supercapacitor fabricated using the composite displayed 83% capacitance retention after 2000 cycles at 3 A g?1 composite. 2023 Taylor & Francis Group, LLC. -
Symmetric supercapacitor based on Co3O4 nanoparticles with an improved specific capacitance and energy density
Metal oxides have garnered significant research interest as highly effective electrode materials for supercapacitors. In this study, we synthesized Co3O4, an electrode material for supercapacitors, utilizing an in-situ hydrothermal method with varying pH levels in the precursor solution. The obtained samples underwent through structural, optical, surface morphological, electrical, and electrochemical analyses, affirming their exceptional suitability for supercapacitor applications. The influence of pH fluctuations in the synthesis process, on the specific capacitance values were analyzed. The X-ray diffraction pattern and Raman spectrum confirmed the normal cubic spinel structure of Co3O4 nanoparticles. The X-ray photoelectron spectrum revealed the chemical bond states of Co3O4. The optical bandgap have been investigated from the Tauc plot. The surface area and morphology were determined through Brunauer Emmett and Teller method and field emission scanning electron microscope images. A high specific capacitance of 1195.05 Fg?1 at a current density of 1.5 Ag?1 was obtained in the three-electrode study for the sample synthesized at a pH of 10. A symmetric supercapacitor (SSC) device was fabricated to facilitate practical analysis. The symmetric supercapacitor device demonstrated a notably elevated specific capacitance of 870.6 Fg?1 at an operational current density of 5 Ag?1, concurrently achieving an enhanced energy density of 77.3 W h/kg and superior power density of 1997.7 W/kg. These performance metrics surpassed those of prior studies in the field. Furthermore, the SSC device exhibited an excellent cyclic stability of 88 % after undergoing 970 charge/discharge cycles. As a result, Co3O4 emerges as a promising and efficient electrode material for applications in supercapacitors. 2024 Elsevier Ltd -
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Symbols as Photographic Texts in the Travel Narratives of Paulo Coelho
Brazilian writer Paulo Coelho de Souzas The Pilgrimage, The Alchemist, Zahir, Aleph and Hippie are known for using literary symbols to describe journeys where the protagonists travel to different destinations searching for something valuable. The author resorted to multiple religions, cultures, traditions, mythologies and folklore to derive inspiration to use those symbols and frame his philosophical thoughts. As the symbols used by Coelho can be deciphered in whatever way subject to personal interpretations, one way of understanding them can be from the perspectives of their already established meanings in religions, cultures, traditions, mythologies and folklore. Such a way of understanding limits the possible meanings that can be derived from those symbols. Moreover, another sign system is known for conveying limited meanings, usually called photographs. Though absolute material accuracy is seen as the hallmark of photography, the meaning of photographs also depends upon their interpretations, and photographic truth is considered a myth. Still, photographs possess documentary properties and convey limited meanings to a large extent. This thesis studied the idea of photography, defining the same by understanding the historical developments in photography over time. Knowing the definition and properties of photographs, it looked at how photographs convey limited meanings and exhibit 'iconic' properties in general. After isolating and studying the literary symbols used by Coelho in the five travel narratives mentioned above using the Peircean model of semiotic analysis, the thesis concludes that symbols act as photographic texts to a certain limit in the five novels, as they tend to move towards becoming 'iconic' from 'symbolic' if understood from the perspectives of their existing meanings in religions, cultures, traditions,mythologies and folklore. -
Symbiotic cyanobacteria in gymnosperms
Cyanobacteria are a widespread group of phototrophic bacteria that are morphologically diverse and present on almost every environment on earth. Many cyanobacteria are able to fix atmospheric nitrogen and thus are able to form symbiotic association with a wide range of eukaryotic hosts such as plants, fungi, sponges, and protists. Cyanobacteria are able to provide carbon to nonphotosynthetic hosts such as fungi, but their primary role is to supply fixed nitrogen to enable the host to flourish in nitrogen poor environments. In turn, cyanobionts get the benefits of protection from competition, predation, and environmental extremes. Of all the cyanobacterial symbiotic associations, this chapter focuses on understanding the symbiotic association between gymnosperm and cyanobacteria. Species belonging to phylum cycadophyta are associated with nitrogen-fixing cyanobacteria (Nostoc species) through small specialized roots called coralloid roots. The cyanobionts are expected to have a heterotrophic mode of carbon nutrition, due to their location in coralloid roots (complete darkness). 2023 Elsevier Inc. All rights reserved. -
SWITCHING INTENTION AND SWITCHING BEHAVIOR OF ADULTS IN THE NON-LIFE INSURANCE SECTOR: MEDIATING ROLE OF BRAND LOVE
In this digital era, customers in the insurance sector always look for better insurance products and services at an affordable price. When customers are unsure about service, they switch over to a better service provider. This behavior is more relevant to non-life insurance. However, the switching behavior of customers is hampered by certain switchover barriers such as brand consciousness, brand pride, brand loyalty, etc. This study focuses on exploring switching intentions and switching behaviors of adults in India keeping brand love as a mediator. A structured questionnaire was employed to collect the primary data from adults having non-life insurance products to analyze switching intentions and switching behaviors. The collected data were analyzed employing SPSS software and Hayes Process Model and appropriate statistical tools. The study results show that the switching intentions of adults vary based on their age, annual income, and education. Mean scores reveal that the lesser the age, the higher the intention to switch over. Further, based on annual income, adults who earn up to Rs 2 lakhs annually have more switching-over intentions (Mean score: 3.9719) followed by adults who earn Rs more than 2 lakhs to 5 lakhs annually (Mean score: 3.7590). Mean scores of education levels regarding switching intentions are higher among more educated adults and less among those who are qualified up to the school level. Arun Kumar N., Girish S., Suresha B., Mahesh E., 2023. -
Switchable surface activity of Bi2Al4O9 nano particles: A contemporary approach in heterocyclic synthesis
Ferroelectric catalysis is emerging as an efficient chemical transformation strategy, especially in the field of clean energy production, wastewater treatment and degradation of pollutants. The core of ferroelectric catalysis is the dynamically switchable electrical polarization on their surface. It enables them to switch their surface activity, more precisely due to binding strength with the substrate. Even though a plethora of reports are available, the introduction of ferroelectric catalytic surfaces for the generation of heterocyclic compounds is a novel aspect. Here, we introduce ferroelectric Bismuthaluminate nanoparticles as catalysts for generating derivatives of azalactone, tetrahydro-benzopyran and pyranopyrazole with improved catalytic efficiency. This can be achieved by switching the direction of polarization of the catalyst which indeed alters the surface electronic states and stimulates the reaction followed by the excellent yield. Here the switchable property is due to the thermally induced polarization of water. Graphical Abstract: [Figure not available: see fulltext.]. 2023, The Author(s), under exclusive licence to Springer Nature B.V. -
Swarm Intelligence Decentralized Decision Making In Multi-Agent System
This research aims to understand how groups of agents can make decisions collectively without relying on a central authority. The research could focus on developing algorithms and models for distributed problem solving, such as consensus-reaching and voting methods, or for coordinating actions among agents in a decentralized manner. The research could also look into the application of these methods in various fields like distributed robotics, swarm intelligence, and multi-agent systems in smart cities and transportation networks. Swarm intelligence in decentralization is an emerging field that combines the principles of swarm intelligence and decentralized systems to design highly adaptive and scalable systems. These systems consist of a large number of autonomous agents that interact with each other and the environment through local communication and adapt their behaviors based on environmental cues. The decentralized nature of these systems makes them highly resilient and efficient, with potential applications in areas such as robotics, optimization, and block chain technology. However, designing algorithms and communication protocols that enable effective interaction among agents without relying on a centralized controller remains a key challenge. This article proposes a model for swarm intelligence in decentralization, including agents, communication, environment, learning, decision-making, and coordination, and presents a block diagram to visualize the key components of the system. The paper concludes by highlighting the potential benefits of swarm intelligence in decentralization and the need for further research in this area. 2023 IEEE. -
Svsl on combination of star with path
Super Vertex Sum Graph is a graph which admits super vertex sum labeling. In this paper, we combine stars and paths under different combinations which results in formation of new graphs and construct algorithm to obtain optimal super vertex sum labeling for the new graphs formed and their super subdivided graphs. 2020 Author(s). -
SVM Ensemble Model for Investment Prediction
International Journal of IT, Engineering and Applied Sciences Research, Vol-1 (2), pp. 19-23. ISSN-2319-4413 -
SVM Ensemble for Insurance Data Analysis
Data mining is the process of analysing data from different perspectives and summarizing it into useful information. Companies with a strong consumer focus use data mining. The information getting from datamining is useful to increase revenue and reduce overall costs of the company. It is applied in retail field, financial sector, communication media, and in marketing organizations. Datamining facilitate these companies to determine relationships among company internal factors such as price, product positioning, or staff skills, and external factors such as competition in products, economic indicators, and customer demographics. Ensemble learning is a machine-learning paradigm where multiple models or learners are trained to solve the problem. This research explores the usage of SVM ensemble for Insurance Data Analysis. The number of Insurance firms is increasing day by day. The main objective of this research is to find out the best policy from a given list of Insurance policies. In this research a detailed study of SVM ensemble is done. An insurance dataset obtained from UCI knowledge discovery in Databases Archive is taken in the research analysis. From the dataset five different Non-life insurance policies were selected and used in this research work. The categories of policies include Fire policy, Home policy, Car policy, Kissan policy and Boat policy. AdaBoost, multiclassifier SVM ensemble was created and tested with the insurance dataset. SVM ensemble produces better accuracy than other ensembles. The knowledge flow of SVM ensemble is loaded in Weka. From each category, the policy that gives a highest accuracy value for SVM ensemble is considered to be the best policy. A graphical user interface is also developed using .NET framework, to view the policy output. This system helps the user to find out a best policy from the analysed data. KEYWORDS: SVM ensemble, Insurance policy, Accuracy, ROC, Support Vector Machine. -
SVM Based AutoEncoder for Detecting Dementia in Young Adults
Dementia's impact on cognitive function necessitates timely diagnosis for effective intervention. Understanding the need for timely detection, the proposed work integrates SVM's decision boundary determination and autoencoder's noise reduction capabilities. The proposed work advances in dementia detection in young adult. Results indicate promising performance, with the model achieving high accuracy around 85.33%. The ROC curve illustrates a balanced trade-off between sensitivity and specificity, while the precision-recall curve highlights effective classification. Importantly, the model surpasses existing literature, underscoring its practical utility. While acknowledging limitations, such as parameter fine-tuning, this study lays the groundwork for refining and expanding this innovative methodology. In summary, this research contributes to the urgent field of early dementia detection, potentially transforming patient care and intervention strategies. 2023 IEEE. -
SVD-CLAHE boosting and balanced loss function for Covid-19 detection from an imbalanced Chest X-Ray dataset
Covid-19 disease has had a disastrous effect on the health of the global population, for the last two years. Automatic early detection of Covid-19 disease from Chest X-Ray (CXR) images is a very crucial step for human survival against Covid-19. In this paper, we propose a novel data-augmentation technique, called SVD-CLAHE Boosting and a novel loss function Balanced Weighted Categorical Cross Entropy (BWCCE), in order to detect Covid 19 disease efficiently from a highly class-imbalanced Chest X-Ray image dataset. Our proposed SVD-CLAHE Boosting method is comprised of both oversampling and under-sampling methods. First, a novel Singular Value Decomposition (SVD) based contrast enhancement and Contrast Limited Adaptive Histogram Equalization (CLAHE) methods are employed for oversampling the data in minor classes. Simultaneously, a Random Under Sampling (RUS) method is incorporated in major classes, so that the number of images per class will be more balanced. Thereafter, Balanced Weighted Categorical Cross Entropy (BWCCE) loss function is proposed in order to further reduce small class imbalance after SVD-CLAHE Boosting. Experimental results reveal that ResNet-50 model on the augmented dataset (by SVD-CLAHE Boosting), along with BWCCE loss function, achieved 95% F1 score, 94% accuracy, 95% recall, 96% precision and 96% AUC, which is far better than the results by other conventional Convolutional Neural Network (CNN) models like InceptionV3, DenseNet-121, Xception etc. as well as other existing models like Covid-Lite and Covid-Net. Hence, our proposed framework outperforms other existing methods for Covid-19 detection. Furthermore, the same experiment is conducted on VGG-19 model in order to check the validity of our proposed framework. Both ResNet-50 and VGG-19 model are pre-trained on the ImageNet dataset. We publicly shared our proposed augmented dataset on Kaggle website (https://www.kaggle.com/tr1gg3rtrash/balanced-augmented-covid-cxr-dataset), so that any research community can widely utilize this dataset. Our code is available on GitHub website online (https://github.com/MrinalTyagi/SVD-CLAHE-and-BWCCE). 2022 Elsevier Ltd