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Tattooing and the Tattoo Number of Graphs
Consider a network D of pipes which have to be cleaned using some cleaning agents, called brushes, assigned to some vertices. The minimum number of brushes required for cleaning the network D is called its brush number. The tattooing of a simple connected directed graph D is a particular type of the cleaning in which an arc are coloured by the colour of the colour-brush transiting it and the tattoo number of D is a corresponding derivative of brush numbers in it. Tattooing along an out-arc of a vertex v may proceed if a minimum set of colour-brushes is allocated (primary colours) or combined with those which have arrived (including colour blends) together with mutation of permissible new colour blends, has cardinality greater than or equal to dG+v. 2020 World Scientific Publishing Company. -
Dynamics of public debt sustainability in major Indian states
This study empirically tests whether the public debt is sustainable or not at 22 major Indian states during 200607 to 201516. It employs the Bohn model for panel data, five alternative specifications and p-spline technique to analyze the issue at aggregate and disaggregate levels. While the results indicate that the debt is sustainable at the aggregate level, it is sustainable only in about 11 states. The results suggest that the fiscal reaction function is linear and the central grant-in aid is an important and a significant undermining factor of sustainability. If the grant-in-aid is excluded from the primary balance, there remain significant positive responses at the aggregate level. However, at the disaggregate level it is significant in only 11 states. Further, the most sustainable states fail to meet the no-Ponzi condition and so the policy intervention is required to improve the debt situation of the states where debt is unsustainable. 2019, 2019 Informa UK Limited, trading as Taylor & Francis Group. -
Computerized grading of brain tumors supplemented by artificial intelligence
For effective diagnosis of health conditions, there is a need to process medical images to obtain meaningful information. The diagnosis of brain tumors begins with magnetic resonance imaging (or MRI) scan. This is followed by segmentation of the medical images so obtained which can prove cumbersome if it were to be performed manually. Determining the best approach to do segmentation remains challenge among multiple computerized approaches. This paper combines both the identification and classification of tumors from the MRI results and is backed by a cloud-based framework to provision the same. The phase of extraction of features includes the utilization of a Hadoop framework and Gabor filter along with variations in terms of orientation and scale. Artificial bee colony algorithm and support vector machine classifier have been used to designate the degree of optimal features and categorize the same. The grading of brain tumors from MRI images can be fulfilled by the aforementioned approach. The said approach is believed to deliver promising results in terms of accuracy, which has also been verified experimentally. 2019, Springer-Verlag GmbH Germany, part of Springer Nature. -
Optimal arrangement of ration items into container using modified forest optimization algorithm
Planning a shrewd framework for loading the ration goods into the container is one of the significant objectives in the mission of smart city advancement in India. This optimal container loading system is designed for the arrangement of ration goods into the container using Modified Forest Optimization algorithm for safe and secure delivery. The effectiveness of the proposed approach has been demonstrated using BR datasets and compared with different optimization algorithms. From the experiment, it is observed that the proposed Modified Forest Optimization algorithm is implemented in java meets the objective of loading the ration items into the container in an optimal fashion. Further, it is observed that the order of arrangement predicted by the proposed algorithm is found to be optimal than other competitive optimization algorithms. 2020, Engg Journals Publications. All rights reserved. -
A Quantum-Inspired Self-Supervised Network model for automatic segmentation of brain MR images
The classical self-supervised neural network architectures suffer from slow convergence problem and incorporation of quantum computing in classical self-supervised networks is a potential solution towards it. In this article, a fully self-supervised novel quantum-inspired neural network model referred to as Quantum-Inspired Self-Supervised Network (QIS-Net) is proposed and tailored for fully automatic segmentation of brain MR images to obviate the challenges faced by deeply supervised Convolutional Neural Network (CNN) architectures. The proposed QIS-Net architecture is composed of three layers of quantum neuron (input, intermediate and output) expressed as qbits. The intermediate and output layers of the QIS-Net architecture are inter-linked through bi-directional propagation of quantum states, wherein the image pixel intensities (quantum bits) are self-organized in between these two layers without any external supervision or training. Quantum observation allows to obtain the true output once the superimposed quantum states interact with the external environment. The proposed self-supervised quantum-inspired network model has been tailored for and tested on Dynamic Susceptibility Contrast (DSC) brain MR images from Nature data sets for detecting complete tumor and reported promising accuracy and reasonable dice similarity scores in comparison with the unsupervised Fuzzy C-Means clustering, self-trained QIBDS Net, Opti-QIBDS Net, deeply supervised U-Net and Fully Convolutional Neural Networks (FCNNs). 2020 Elsevier B.V. -
Smart Metering System with Google Assistant
This paper presents a unique research problem in the area of automation system by using IoT. The mentioned approach utilizes Google assistant, which is incorporated within Google home which uses voice-controlled inputs and voice feedbacks. This paper discusses a new method to develop a smart energy meter at a distributor level and to make use of this technology to monitor the power consumption of each device individually which can help the user to monitor the electricity usage in real time and thus helps to save electricity and reduce cost on your electricity bill. 2020, Asian Research Association. All rights reserved. -
Lightweight Spectral-Spatial Squeeze-and- Excitation Residual Bag-of-Features Learning for Hyperspectral Classification
Of late, convolutional neural networks (CNNs) find great attention in hyperspectral image (HSI) classification since deep CNNs exhibit commendable performance for computer vision-related areas. CNNs have already proved to be very effective feature extractors, especially for the classification of large data sets composed of 2-D images. However, due to the existence of noisy or correlated spectral bands in the spectral domain and nonuniform pixels in the spatial neighborhood, HSI classification results are often degraded and unacceptable. However, the elementary CNN models often find intrinsic representation of pattern directly when employed to explore the HSI in the spectral-spatial domain. In this article, we design an end-to-end spectral-spatial squeeze-and-excitation (SE) residual bag-of-feature (S3EResBoF) learning framework for HSI classification that takes as input raw 3-D image cubes without engineering and builds a codebook representation of transform feature by motivating the feature maps facilitating classification by suppressing useless feature maps based on patterns present in the feature maps. To boost the classification performance and learn the joint spatial-spectral features, every residual block is connected to every other 3-D convolutional layer through an identity mapping followed by an SE block, thereby facilitating the rich gradients through backpropagation. Additionally, we introduce batch normalization on every convolutional layer (ConvBN) to regularize the convergence of the network and scale invariant BoF quantization for the measure of classification. The experiments conducted using three well-known HSI data sets and compared with the state-of-the-art classification methods reveal that S3EResBoF provides competitive performance in terms of both classification and computation time. 1980-2012 IEEE. -
Role of mesoporous silica supported mixed oxides of ceria and samaria for the synthesis of ?-caprolactone at room temperature
Mesoporous silica was prepared from rice husk by pyrolysis method. Mixed oxides of ceria and samaria (50/50) were disp?ersed on silica by rotavapor assisted wet impregnation method. Catalysts were further modified by doping with MoO3, La2O3 and mixed MoO3La2O3. The prepared systems were characterized by various physicochemical techniques such as BET surface area analysis, scanning electron microscopy, elemental detection analysis, transmission electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, Thermogravimetric analysis, n-butylamine titration and X-ray photoelectron spectroscopy analysis. The catalytic activity of all the systems were studied in the oxidation of cyclohexanone to ?-caprolactone. Various parameters such as time, molar ratio of cyclohexanoneH2O2, temperature, solvent and the amount of catalyst were studied thoroughly to optimize the favorable conditions for the oxidation reaction. Higher ?-caprolactone selectivity of 88.9% was observed in the presence of hydrogen peroxide in acetonitrile medium. The recyclability tests were performed up to six cycles without any appreciable loss in activity, which confirmed the stability of the prepared systems. Good yield with high selectivity was achieved at room temperature, which makes the protocol greener. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
Highly Efficient Photocatalytic Conversion of Amine to Amide and Degradation of Methylene Blue Using BiOClTiO2 Nano Heterostructures
Abstract: Facile green synthesis of BiOClTiO2 was done using combustion technique by Ixora coccinea leaf extract as fuel source. The said material was characterized using XRD, SEM, EDX, HRTEM, SAED, FTIR, and UV-DRS. The particle size was found to be approximately 60nm and a crystallite size of 0.3nm from TEM. The photocatalytic activity of the material was found out using photoluminescence studies, dye degradation and photocatalytic organic conversion. The material showed excellent dye degradation capacity for methylene blue with 80% of the dye degraded under 3hrs. The stabilisation of electronhole pair by the heterostructure gave it the ability to perform easy degradation. The degradation kinetics have also been studied. It also showed an excellent organic conversion property with formylation yield reaching up to 96% and total conversion of the reactant molecule. The material is a potent photocatalyst due to its great efficiency and can have a remarkable role in the synthesis of important organic molecules and detoxification of environment. Graphical Abstract: The heterostructure catalyses the conversion of amine to amides and mineralizes methylene blue under visible light condition. [Figure not available: see fulltext.]. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
Extraction of Graphene Nanostructures from Colocasia esculenta and Nelumbo nucifera Leaves and Surface Functionalization with Tin Oxide: Evaluation of Their Antibacterial Properties
Expeditious evolution of antimicrobial resistance in recent years has been identified as a growing concern by various health organizations around the world. Herein, facile and environmentally benign production of highly antibacterial carbonaceous nanomaterials from Colocasia esculenta and Nelumbo nucifera leaves is reported. After carbonization and oxidative treatment, smaller graphene domains are formed in Colocasia esculenta derivatives, whereas larger sheetlike structures are observed in the case of Nelumbo nucifera. Smaller particle size makes quantum confinement effects more prominent, as is evident in fine-tuning of the photoluminescence emission after each stage of treatment. The influence of precursor materials on the antibacterial properties of the nanosystems is also demonstrated. When microbiocidal activity was tested against model bacteria Pseudomonas aeruginosa, the nanocomposite derived from Colocasia esculenta leaves showed higher activity than the antibiotic drug clarithromycin (control) with a measured zone of inhibition of 400.5 mm. This is one of the highest values reported in comparison with plant-based carbonsilver nanosystems. Quantitative analysis revealed that the nanocomposite obtained from Colocasia esculenta leaves has antimicrobial efficacy equivalent to those of commercial antibiotic drugs and is able to eradicate bacteria at much lower concentrations than that obtained from Nelumbo nucifera leaves. 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim -
Effect of surface charge and other critical parameters on the adsorption of dyes on SLS coated ZnO nanoparticles and optimization using response surface methodology
Adsorption is a possible method with distinct advantages to remediate pollution due to dyes. Sodium Lauryl Sulfate (SLS) coated ZnO nanoparticles were synthesized using the electrochemical method. The final product was dried at different temperatures, 60, 120, 150 and 300 C. The sample dried at 60 C was found to have the maximum SLS coating on its surface providing high negative charge density. This facilitates the adsorption of cationic dyes on its surface through electrostatic attraction. The effect of SLS on the adsorption process was confirmed by comparing it with ZnO without SLS. The effect of important parameters such as amount of adsorbent, concentration of dye, temperature and time on the percentage of adsorption was investigated using Box-Behnken design (BBD) of Response Surface Methodology (RSM). The prepared catalysts were characterized using X-ray diffraction analysis, infrared spectroscopic analysis, scanning electron microscopy, elemental detection analysis, thermogravimetric and zeta potential analysis. Finally, the study was extended to Langmuir and Freundlich isotherms in order to confirm the type of adsorption. The adsorption kinetics studies showed that it obeys pseudo second order kinetics. 2020 Elsevier Ltd. -
Examining the relationship between e-service recovery quality and e-service recovery satisfaction moderated by perceived justice in the banking context
Purpose: The study focuses on the core issue faced by bankers on how to retain existing customers who have encountered an e-service failure and who are skeptical about the justice received through the service recovery process. It further endeavors to create an internal bench-marking model for assessing e-service recovery satisfaction. Design/methodology/approach: By the experimental study, the authors confirm a measurement model using structural equation modeling for examining the impact of perceived service recovery quality antecedents on e-service recovery satisfaction moderated by perceived justice. In total, responses from 399 e-banking customers, who had experienced a e-service failure, were recorded using a 5-point Likert scale with a structured questionnaire. Findings: The perceived e-service recovery quality antecedents identified were perceived information quality, digital commitment, perceived employee performance and perceived service orientation of organization. The empirical results revealed that perceived information quality was the most significant predictor of e-service recovery satisfaction. Perceived justice moderates the relation between perceived service recovery quality and e-service recovery satisfaction. Research limitations/implications: The research does not contemplate the e-service recovery satisfaction of customers who have undergone multiple service failures. Practical implications: The conclusions of the investigation suggest that the four antecedents of perceived e-service recovery quality model are suitable instruments for creating benchmarks for e-service recovery satisfaction for banks, and that perceived justice moderates the relationship between e-service recovery quality and e-service recovery satisfaction. Therefore, policymakers in banks can use this model to assess the e-service recovery quality, and they ought to enhance the perceived justice feel of the customers who have experienced a service failure. Originality/value: There remains scarcity of empirical research focusing on perceived information quality and digital commitment as antecedents of perceived e-service recovery quality and its effect on e-service recovery satisfaction in the banking context. Furthermore, similar studies within the banking sector have rarely considered perceived justice as a moderator variable. Hence, this paper attempts to accomplish the research gap by empirically testing the e-service recovery satisfaction level of a large sample of the population toward four antecedents of perceived e-service recovery quality rendered by banks and create a benchmark model to ascertain e-service recovery satisfaction. 2020, Emerald Publishing Limited. -
Directional Vector-Based Skin Lesion Segmentation - A Novel Approach to Skin Segmentation
Efficient skin lesion segmentation algorithms are required for computer aided diagnosis of skin cancer. Several algorithms were proposed for skin lesion segmentation. The existing algorithms are short of achieving ideal performance. In this paper, a novel semi-automatic segmentation algorithm is proposed. The fare concept of the proposed is 8-directional search based on threshold for lesion pixel, starting from a user provided seed point. The proposed approach is tested on 200 images from PH2 and 900 images from ISBI 2016 datasets. In comparison to a chosen set of algorithms, the proposed approach gives high accuracy and specificity values. A significant advantage of the proposed method is the ability to deal with discontinuities in the lesion. 2020 World Scientific Publishing Company. -
Analysis of a magnetic field and Hall effects in nanoliquid flow under insertion of dust particles
In this study, the two-phase hydromagnetic flow of a viscous liquid through a suspension of dust and nanoparticles is considered. The influence of the Hall current is also taken into account. The similarity variables are utilized to transform the problem into one independent variable. The obtained expressions in one independent variable are solved through the RungeKuttaFehlberg scheme connected with the shooting procedure. The computed results are sketched for employing multiple values of physical constraints on the temperature and velocity of the nanofluid and dust phase. The characterization of various nanoparticles like Cu, Al2O3, TiO2, and Ag on velocities and temperatures of both phases is made through plots. A comparative analysis in the limiting approach is presented to justify the present solution methodology. The range of emerging parameters is taken as 0 ? l ? 3, 0.1 ? ?t ? 3, 0 ? m ? 2.5, 0 ? M2 ? 2, 0.1 ? ?v ? 3, 0 ? ? ? 0.4, and ?0.8 ? ? ? 0.8. From the study, it is revealed that ?t has theopposite effect on the temperature of dust and nanofluid phases. The Hall parameter mraisesthe profiles of velocities in the nanoliquid and dust phases. Also, it is found that the transverse velocities h(?) and H((?) andtemperatures ?(?) and ?p(?) rise for larger ?. 2020 Wiley Periodicals, Inc. -
Exploring the role of E-servicescape dimensions on customer online shopping: A stimulus-organism-response paradigm
With limited empirical evidence and an incomplete understanding of e-servicescape environment, its effects on e-commerce websites still needs to be explored. Hence, the study understands and assesses the effects of e-servicescape environment on customer purchase behavior, considering the moderating role of gender. The stimulus-organism-response framework was adapted to formulate a conceptual model, in which the e-servicescape (stimulus) features were modelled as an antecedent of customer trust (organism) on website that directs customer behaviour of purchase intention (response). To conduct an analysis, a data sample of 304 responses was collected from those who have earlier used e-commerce websites using a structural equation modelling technique. Results of the study shows that e-servicescape dimensions are a strong predictor of trust that strongly impacts customer purchase intention. Results further reveal that in an online environment, the gender gap is depleting as it impacts all three dimensions of the e-servicescape on customer behavior which remains consistent for both groups. Copyright 2020, IGI Global. -
Impact of Voluntary Disclosure on Valuation of Firms: Evidence from Indian Companies
This article investigates the effect of voluntary corporate disclosures on the firm value from the market value perspective. Financial reporting includes disclosures as prescribed by regulators, but few companies go beyond mandatory requirements and provide additional information voluntarily. This study empirically tests the extent of such voluntary disclosures using Corporate Voluntary Disclosure Index containing 81 items of both financial and non-financial information and panel data regression to test the hypotheses. The sample for this study is the non-financial companies in the BSE 100 Index and the period is five financial years from 20102011 to 20142015. This study finds a positive association between voluntary disclosures and firm value as measured by Tobins Q. Especially the market gives a higher valuation for companies disclosing optional information on social and environmental, corporate governance and financial information. This finding has a significant implication for emerging economies like India and it supports various disclosure theories such as agency, stakeholders and positive accounting theories. 2020 Management Development Institute. -
Enhancement of free convection from horizontal-base straight-fin heat sink by partial shrouding
This work presents a simple method to improve natural convection heat transfer performance of horizontal-base straight-fin heat sink by adding partial shroud plates on top of the heat sink at both ends. Experiments are conducted in conjunction with a detailed three-dimensional (3D) computational study. The numerical model is validated using experimental results. With partial shrouding, the modification and effective utilization of airflow surrounding the heat sink leads to significant heat transfer enhancement. The installation of shroud plates effectively improves the mass flowrate of air admitted into the fin channel. Further, the airflow drawn above the heat sink dissipates heat from the upper surface of the shroud plate. There is also a significant heat dissipation from the lower surface of the shroud plate which is exposed to cold air drawn from the side-end of the heat sink. The heat transfer from the existing optimal conventional heat sink is improved by 17% with the introduction of shroud plates. An optimal width of the shroud plate is identified to exist for the maximum heat transfer. The percentage enhancement in heat transfer achieved by partial shrouding increases with a decrease in the fin height and with an increase in the fin spacing. The proposed compact heat sink design would be of application in enhancing passive heat dissipation from light-emitting diode (LED) lights and other electronic devices, especially when size constraints exist. Copyright 2020 by ASME -
Augmented Reality-Enabled Education for Middle Schools
Augmented reality acts as an add-on to teachers while teaching students, and this helps the teachers and students to have an interactive session. Augmented realitys usage in education is cited as one of the major changes in the educational sector. Thus, the work carried out makes a positive impact in the educational industry. Augmented reality provides features like image recogntion, motion tracking, facial recognition, plane detection, etc., to provide interactive sessions. Simultaneous localization and mapping and concurrent odometry and mapping have proved to be efficient algorithms for augmented reality on mobile devices. The work carried out allows students to view interactive newspapers while reading a specific article. It also allows them to view a dynamic three-dimensional model of the solar system on their smartphone using augmented reality. 2020, Springer Nature Singapore Pte Ltd. -
Acetylcholine esterase inhibition activity of leaf extract of Saraca asoca using zebrafish as model organism
Alzheimers disease, also called as Senile Dementia, is a progressive neurogenerative disease that slowly destroys important mental functions like memory, reasoning and thinking. A plethora of factors including genetics, lifestyle, environment, age etc. play a part in determining its incidence. One of the commonly used techniques to slow down the progression of Alzheimers is to reduce the functioning of Acetylcholinesterase (AChE) enzyme which breaks down the neurotransmitter acetylcholine. Plants have been found to be natural sources of AChE inhibitors. Hence the present investigation was an attempt to screen Ashoka plant (Saraca asoca) for such inhibitors. Zebrafish (Danio rerio) was used as a model organism due to its genetic similarities with humans. Both in vivo and in vitro analyses using zebrafish indicated inhibitory action of the leaf extract on AChE. Gas Chromatography- Mass spectrometry (GCMS) analysis of the methanolic leaf extract and further docking studies of prominent phytochemicals revealed the AChE inhibitory potential of molecules like Stigmasterol, ?-sitosterol, Vitamin E etc. Hence these molecules can be thought of as targets in the therapy of Alzheimers disease. 2020 World Research Association. All rights reserved. -
Psychological health among armed forces doctors during COVID-19 pandemic in India
Background: A pandemic poses a significant challenge to the healthcare staff and infrastructure. We studied the prevalence of anxiety and depressive symptoms among armed forces doctors in India during the COVID-19 pandemic and the factors that contribute to these symptoms. Methods: The study was conducted from March 30, 2020, to April 2, 2020, using a self-administered questionnaire questionnaire using the hospital anxiety and depression scale (HADS), which was sent through Google Forms. Responses were received from 769 respondents. Data were analyzed for demographic details and HADS scores using the chi-square test and backward logistic regression. Results: Anxiety and depressive symptoms were seen in 35.2% and 28.2% of the doctors, respectively. In doctors with anxiety symptoms, significant associations were observed with age (2035 years, 39.4%, P = 0.01), gender (females, 44.6%, P < 0.001), duration of service (010 years, 38%, P = 0.03), and clinical versus non-clinical specialties (non-clinical, 41.3%, P < 0.001) as opposed to marital status, education level, and current department of work. In doctors with depressive symptoms, significant associations were observed with age (P = 0.04), clinical versus non-clinical specialties (P < 0.001), duration of service (010 years, 30.1%, P = 0.03), and doctoral degree (P = 0.04) as opposed to gender, marital status, education level, and current working department. Conclusion: The study revealed a high prevalence of anxiety and depressive symptoms among armed forces doctors. The main contributing factors are female gender, young age group, non-clinical specialties, and having a doctoral degree. Copyright 2020 Indian Psychiatric Society - South Zonal Branch.