Browse Items (11810 total)
Sort by:
-
An Image Quality Selection and Effective Denoising on Retinal Images Using Hybrid Approaches
Retinal image analysis has remained an essential topic of research in the last decades. Several algorithms and techniques have been developed for the analysis of retinal images. Most of these techniques use benchmark retinal image datasets to evaluate performance without first exploring the quality of the retinal image. Hence, the performance metrics evaluated by these approaches are uncertain. In this paper, the quality of the images is selected by utilizing the hybrid naturalness image quality evaluator and the perception-based image quality evaluator (hybrid NIQE-PIQE) approach. Here, the raw input image quality score is evaluated using the Hybrid NIQE-PIQE approach. Based on the quality score value, the deep learning convolutional neural network (DCNN) categorizes the images into low quality, medium quality and high quality images. Then the selected quality images are again pre-processed to remove the noise present in the images. The individual green channel (G-channel) is extracted from the selected quality RGB images for noise filtering. Moreover, hybrid modified histogram equalization and homomorphic filtering (Hybrid G-MHE-HF) are utilized for enhanced noise filtering. The implementation of proposed scheme is implemented on MATLAB 2021a. The performance of the implemented method is compared with the other approaches to the accuracy, sensitivity, specificity, precision and F-score on DRIMDB and DRIVE datasets. The proposed schemes accuracy is 0.9774, sensitivity is 0.9562, precision is 0.99, specificity is 0.99, and F-measure is 0.9776 on the DRIMDB dataset, respectively. 2023 Baqiyatallah University of Medical Sciences. All rights reserved. -
Coronal Elemental Abundances During A-Class Solar Flares Observed by Chandrayaan-2 XSM
The abundances of low first ionization potential (FIP) elements are three to four times higher in the closed loop active corona than in the photosphere, known as the FIP effect. Observations suggest that the abundances vary in different coronal structures. Here, we use the soft X-ray spectroscopic measurements from the Solar X-ray Monitor (XSM) onboard the Chandrayaan-2 orbiter to study the FIP effect in multiple A-class flares observed during the minimum of Solar Cycle 24. Using time-integrated spectral analysis, we derive the average temperature, emission measure, and the abundances of four elements Mg, Al, Si, and S. We find that the temperature and emission measure scales with the sub-class of flares while the measured abundances show an intermediate FIP bias for the lower A-flares (e.g. A1), while for the higher A-flares, the FIP bias is near unity. To investigate it further, we perform a time-resolved spectral analysis for a sample of the A-class flares and examine the evolution of temperature, emission measure, and abundances. We find that the abundances drop from the coronal values towards their photospheric values in the impulsive phase of the flares and, after the impulsive phase, they quickly return to the usual coronal values. The transition of the abundances from the coronal to photospheric values in the impulsive phase of the flares indicates the injection of fresh unfractionated material from the lower solar atmosphere to the corona due to chromospheric evaporation. However, explaining the quick recovery of the abundances from the photospheric to coronal values in the decay phase of the flare is challenging. 2023, The Author(s), under exclusive licence to Springer Nature B.V. -
Murraya koenigii extract blended nanocellulose-polyethylene glycol thin films for the sustainable synthesis of antibacterial food packaging
Non-biodegradable plastics are a worldwide problem that have a negative impact on all living things, including humans. Nanocellulose, an excellent biopolymer is known for their increasing uses in food, healthcare, cosmetics, and various other fields. Nanocellulose is readily biodegradable, bioderived, and useful for creating innovative bioplastics that are employed in the production of food packaging and wound dressing. Curry leaves (Murraya koenigii) belongs to the rutaceae family and has many health benefits. Synthesis of Murraya koenigii incorporated nanocellulose thin films, and its characterisation using FT-IR, and XRD is discussed in detail. The source of nanocellulose in this study is sugar cane bagasse, an easily available agricultural residue in Kerala. Also, a biocompatible plasticizer is utilised to produce antibacterial packaging for food. The synthesised nanocomposites showed non-toxicity against THP1-derived macrophage cells and significant antibacterial activity against gram positive and gram-negative bacteria suggesting the possible application as a viable alternative for food packaging materials. 2023 Elsevier B.V. -
Analysis of the Effectiveness of a Two-Stage Three-Phase Grid-Connected Inverter for Photovoltaic Applications
This paper proposes a two-stage three-phase grid-connected inverter for photovoltaic applications. The proposed inverter topology consists of a DC-DC boost converter and a three-phase grid-connected inverter. The DC-DC boost converter is used to boost the low voltage DC output of the PV array to a high voltage DC level that is suitable for feeding into the grid-connected inverter. The three-phase grid-connected inverter is used to convert the high voltage DC output of the boost converter into a three-phase AC output that is synchronized with the grid voltage. The proposed inverter topology offers several advantages over traditional single-stage inverters. Firstly, the DC-DC boost converter allows for the use of a smaller, more efficient inverter in the second stage, reducing the overall cost of the system. Secondly, the use of a boost converter allows for the maximum power point tracking of the PV array, which can increase the overall efficiency of the system. The proposed inverter topology offers improved control of the grid current, reducing the impact of the PV system on the grid. The proposed topology has been simulated using MATLAB/Simulink and the results show that the system is capable of delivering a high-quality three-phase AC output with low harmonic distortion. The Author(s). Publisher: University of Tehran Press. -
Design and Development of Multi-Sensor ADEP for Bore Wells Integrated with IoT Enabled Monitoring Framework
Typically, about 51% of the groundwater satisfies the drinking water worldwide and is regarded as the major source for the purpose of irrigation. Moreover, the monitoring and assessment of groundwater over bore wells is essential to identify the effect of seasonal changes, precipitations, and the extraction of water. Hence, there is a need to design a depth sensor probe for bore wells so as to analyze/monitor the quality of underground water thereby estimating any geophysical variations like landslides/earthquakes. Once the depth sensor probe is designed, the data is collected over wireless sensor network (WSN) medium and is stored in cloud for further monitoring and analyzing purposes. WSN is the major promising technologies that offer the real-time monitoring opportunities for geographical areas. The wireless medium in turn senses and gathers data like rainfall, movement, vibration, moisture, hydrological and geological aspects of soil that helps in better understanding of landslide or earthquake disasters. In this paper, the design and development of geophysical sensor probe for the deep bore well so as to monitor and collect the data like geological and hydrological conditions. The data collected is then transmitted by wireless network to analyze the geological changes which can cause natural disaster and water quality assessment. 2023 The Authors. Published by AnaPub Publications. This is an open access article under the CC BY-NC-ND license. (http://creativecommons.org/licenses/by-nc-nd/4.0/) -
Building Global Teaching Capacity Among Pre-Service Teachers: Epistemological and Positional Framing in an Internationally Paired, Authentic Practicum
Building the capacity of pre-service teachers to work in globalized cross-cultural environments is essential to cope with the challenges of the 21st century. This study establishes the value of internationally paired, authentically collaborative practicums with strong epistemological and positional framing in pursuing such capacity development. It was conducted among 90 pre-service teachers from three different universities in Australia and India who participated in a three-week paired practicum in three schools in India. The practicum included the collaborative production of an integrated Australian and Indian combined theme presented in a whole school forum. Mixed methods and a design-based research approach yielded data affirming that such a model did indeed provide pre-service teachers with the confidence to teach in increasingly diverse classrooms and contexts, while also identifying which aspects of this practicum model were most influential in this regard. 2021 European Association for International Education. -
Machine Learning with Data Science-Enabled Lung Cancer Diagnosis and Classification Using Computed Tomography Images
In recent times, the healthcare industry has been generating a significant amount of data in distinct formats, such as electronic health records (EHR), clinical trials, genetic data, payments, scientific articles, wearables, and care management databases. Data science is useful for analysis (pattern recognition, hypothesis testing, risk valuation) and prediction. The major, primary usage of data science in the healthcare domain is in medical imaging. At the same time, lung cancer diagnosis has become a hot research topic, as automated disease detection poses numerous benefits. Although numerous approaches have existed in the literature for lung cancer diagnosis, the design of a novel model to automatically identify lung cancer is a challenging task. In this view, this paper designs an automated machine learning (ML) with data science-enabled lung cancer diagnosis and classification (MLDS-LCDC) using computed tomography (CT) images. The presented model initially employs Gaussian filtering (GF)-based pre-processing technique on the CT images collected from the lung cancer database. Besides, they are fed into the normalized cuts (Ncuts) technique where the nodule in the pre-processed image can be determined. Moreover, the oriented FAST and rotated BRIEF (ORB) technique is applied as a feature extractor. At last, sunflower optimization-based wavelet neural network (SFO-WNN) model is employed for the classification of lung cancer. In order to examine the diagnostic outcome of the MLDS-LCDC model, a set of experiments were carried out and the results are investigated in terms of different aspects. The resultant values demonstrated the effectiveness of the MLDS-LCDC model over the other state-of-The-Art methods with the maximum sensitivity of 97.01%, specificity of 98.64%, and accuracy of 98.11%. 2023 World Scientific Publishing Company. -
An improved frequent pattern tree: the child structured frequent pattern tree CSFP-tree
Frequent itemsets are itemsets that occur frequently in a dataset. Frequent itemset mining extracts specific itemsets with supports higher than or equal to a minimum support threshold. Many mining methods have been proposed but Apriori and FP-growth are still regarded as two prominent algorithms. The performance of the frequent itemset mining depends on many factors; one of them is searching the nodes while constructing the tree. This paper introduces a new prefix-tree structure called child structured frequent pattern tree (CSFP-tree), an FP-tree attached with a child search subtree to each node. The experimental results reveal that the CSFP-tree is superior to the FP-tree and its new variations for any kind of datasets. 2022, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature. -
Subspace spanning graph topological spaces of graphs
A collection of spanning subgraphs TS, of a graph G is said to be a spanning graph topology if it satisfies the three axioms: (Formula Presented) where, n = |V (G)|, the collection is closed under any union and finite intersection. Let (X, T ) be a topological space in point set topology and Y ? X then, TY = {U ? Y: U ? T } is a topological space called a subspace topology or relative topology defined by T on Y. In this paper we discusses the subspace spanning graph topology defined by the graph topology TS on a spanning subgraph H of G. 2023, Proyecciones. All Rights Reserved. -
Phytochemical Composition, Bioactive Compounds, and Antioxidant Properties of Different Parts of Andrographis macrobotrys Nees
Andrographis macrobotrys Nees is an ethnomedicinal plant belonging to the family Acanthaceae, distributed in the moist deciduous and semi-evergreen forests of the southern Western Ghats of India. The objective of this research was to determine the phytochemical composition and bioactive chemical components using gas chromatography and mass spectrometry (GC-MS) and to check the antioxidant potential of the plant part extracts. A. macrobotrys roots, stems, and leaves were obtained from the species natural habitat in the Western Ghats, India. The bioactive compounds were extracted using a Soxhlet extractor at 5560 C for 8 h in methanol. Identification analysis of A. macrobotrys bioactive compound was performed using GC-MS. Quantitative estimation of phytochemicals was carried out, and the antioxidant capacity of the plant extracts was determined by 2,2?-diphenyl-1-picrylhydrazyl radical scavenging (DPPH) and ferric reducing assays (FRAP). A. macrobotrys has a higher concentration of phenolics in its stem extract than in its root or leaf extracts (124.28 mg and 73.01 mg, respectively), according to spectrophotometric measurements. GC-MS analysis revealed the presence of phytochemicals such as azulene, 2,4-di-tert-butylphenol, benzoic acid, 4-ethoxy-ethyl ester, eicosane, 3-heptadecanol, isopropyl myristate, hexadecanoic acid methyl ester, hexadecanoic acid, 1-butyl-cyclohexanol, 9,12-octadecadienoic acid, alpha-monostearin, and 5-hydroxy-7,8-dimethoxyflavone belonging to various classes of flavonoids, terpenoids, phenolics, fatty acids, and aromatic compounds. Significant bioactive phytochemicals include 2,4-di-tert-butylphenol, 2-methoxy-4-vinylphenol, 5-hydroxy-7,8-dimethoxyflavone, azulene, salvigenin, squalene, and tetrapentacontane. In addition, the antioxidant capability of each of the three extracts was assessed. The stem extract demonstrated impressive DPPH scavenging and ferric reduction activities, with EC50 values of 79 mg/mL and 0.537 0.02 OD at 0.2 mg/mL, respectively. The results demonstrated the importance of A. macrobotrys as a source of medicine and antioxidants. 2023 by the authors. -
A ratiometric fluorescent sensor based on dual-emissive carbon dot for the selective detection of Cd2+
Cadmium (Cd2+), a heavy metal ion used in numerous industries, has toxic adverse effects on the environment; it is crucial to develop a quick and reliable method for Cd2+ determination. Fluorescent biomass-derived carbon quantum dots (CD) with rich carboxyl groups on the surface were synthesized using water amaranth leaves by hydrothermal method with a 12.1% quantum yield. The surface of CD was further modified with 1-pyrene carboxaldehyde (PC) to synthesize pyrene carboxaldehyde-carbon quantum dots (PC-CD). This study developed a fluorescent ratiometric nanosensor using a covalently functionalized CD with pyrene derivative and demonstrates highly selective identification capability towards Cd2+ over competing metal ions. The Nano sensor has significant selectivity towards Cd2+ in an excellent linear range of 0-70 ?M with a detection limit as low as 15 nM and demonstrates excellent water solubility and biocompatibility. Transmission electron spectroscopy (TEM), Fourier Transform infrared spectroscopy (FT-IR), and X-ray photon spectroscopy (XPS) were used to identify the surface functionalization of PC-CD. Finally, the developed ratiometric sensor was used for detecting Cd2+ metal ions from various water effluents. 2023 Elsevier Ltd. -
Comparison of the effect of suction-injection-combination on Rayleigh-Bard convection in the case of asymmetric boundaries with those of symmetric ones
The effect of suction-injection-combination (SIC) on the linear and weakly nonlinear stability of Rayleigh-Bard convection is considered in the paper for the cases of symmetric and asymmetric boundary conditions. Using the Maclaurin series with an appropriate number of terms, expression for eigenfunctions is obtained. The linear theory corroborates the results obtained using the chosen eigenfunctions in the limiting case of the no-SIC effect by matching accurately with the exact values concerning the critical Rayleigh number (Rac) and the wave number (?c). It is found that the effect of SIC is to stabilize the system in the case of symmetric boundaries irrespective of SIC being pro-gravity or anti-gravity. However, the effect of SIC is to stabilize/destabilize the system depending on SIC being pro-gravity or anti-gravity in the case of the asymmetric boundaries. We also noted a similar effect in the case of ?c wherein a maximum error of order 10 ? 4 was observed. The main novelty of the present work is studying the influence of SIC on the nonlinear dynamics of the considered problem. It is shown that the effect of SIC is to hasten the onset of chaos. Using various indicators (the largest Lyapunov exponent, the time series solution, the amplitude spectrum, and the phase-space plots), the dynamical behavior of the system is analyzed and the influence of SIC on the dynamics is recorded. The change due to the boundary effect and the SIC on the size of convection rolls and the trapping region where the dynamical system evolves within a bound is highlighted in the paper. 2023 Author(s). -
Exploring chatbot trust: Antecedents and behavioural outcomes
An awareness about the antecedents and behavioural outcomes of trust in chatbots can enable service providers to design suitable marketing strategies. An online questionnaire was administered to users of four major banking chatbots (SBI Intelligent Assistant, HDFC Bank's Electronic Virtual Assistant, ICICI bank's iPal, and Axis Aha) in India. A total of 507 samples were received of which 435 were complete and subject to analysis to test the hypotheses. Based on the results, it is found that the hypothesised antecedents, except interface, design, and technology fear factors, could explain 38.6% of the variance in the banking chatbot trust. Further, in terms of behavioural outcomes chatbot trust could explain, 9.9% of the variance in customer attitude, 11.4% of the variance in behavioural intention, and 13.6% of the variance in user satisfaction. The study provides valuable insights for managers on how they can leverage chatbot trust to increase customer interaction with their brand. By proposing and testing a novel conceptual model and examining the factors that impact chatbot trust and its key outcomes, this study significantly contributes to the AI marketing literature. 2023 The Authors -
Kunde Habba The Profane and the Sacred
[No abstract available] -
Design of decision support system to identify crop water need
Crop Water Need (ET crop) is referred to as the amount of water needed by a crop to grow. ET crop has high significance to identify the adequate amount of irrigation need. In this paper, a decision support system is proposed to identify Crop Water Need. The proposed decision support system is implemented through sensors and android based smartphone. Internet of Things (IoT) based temperature sensor (DHT11) is used to acquire the real time environmental factors that affect the ET crop. The sensor will communicate with android based smartphone application using Bluetooth Technology (BT-HC05). This proposed system has been compared with available evapotranspiration and existing manual method of evapotranspiration and it was found that proposed system is more correlated than existing manual method of evapotranspiration. The correlation coefficient obtained between proposed system and available evapotranspiration is 0.9783. The proposed decision support system is beneficial for farmers, agriculture researchers and professionals. 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
A novel survey for young substellar objects with the W-band filter IV: detection and characterization of low-mass brown dwarfs in Serpens Core
We present spectroscopic confirmation of nine M5 or later Serpens Core candidate members, identified using a combination of CFHT WIRCam photometry and IRTF SpeX spectroscopy. Through spectral fitting, we find that the latest of these nine candidate members is best fit by an L0 spectral standard (in the range of M8L2), implying a mass of ?0.010.035M?. If confirmed as a cluster member, this would be one of the lowest mass Serpens Core objects ever discovered. We present analysis of the physical properties of the sample, as well as the likely membership of the candidate Serpens Core members. 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
Stratified Bioconvective Jet Flow of Williamson Nanofluid in Porous Medium in the Presence of Arrhenius Activation Energy
Due to the higher coefficients of heat and mass transfer, the jet flow has become an effective source for the transfer of heat and mass in various industries. Due to these high coefficients, the heat and mass transfer rates will be high in the appliances equipped with the jet flow. Further, the existence of the magnetic field helps in controlling the velocity and the presence of the gyrotactic microorganisms ensure proper mixing of nanoparticles. A dilute nanoparticle suspension is assumed so that it will not affect the movement of motile cells that leads to bioconvection. Hence, this paper aims to analyze the characteristics of heat transfer as well as mass transfer of the jet flow of Williamson nanofluid past a porous stretching sheet in the existence of microorganisms. The mathematical model obtained as a result of these assumptions is transformed into nonlinear ordinary differential equations for which acceptable solutions are obtained using the numerical method. The results thus obtained are presented graphically and based on the outcomes, it is perceived that the magnetic field has control over the velocity profile thus influencing the thermal profile. The increase in the Williamson parameter also reduces the velocity of the fluid flow. Further, an increase was noticed in the thermal and concentration profiles of the nanofluid for higher values of thermophoresis parameter and the increase in the porosity reduced the speed of the flow of nanofluid. 2023 World Scientific Publishing Company. -
Protection of Artificial Intelligence Autonomously Generated Works under the Copyright Act, 1957-An Analytical Study
Artificial Intelligence (AI) is not new anymore; it has become a new normal. In the present 3A era (Advanced, automated and autonomous), the Next Rembrandt paintings, Shimons lyrics and songs and Bot Dylans Irish folk songs are the works generated by the AI without any considerable human contribution. In the US, the Copyright Act, 1976 does not protect the works generated independently by the AI without human intervention and thus dropping such works in the public domain immediately after their creation. However, in the UK, the Copyright, Patents and the Designs Act, 1988 under Section 9 (3) attributes copyright to the person by whom the arrangements necessary for the creation of the work are undertaken in case of AI generated works. India has taken a giant leap by considering AI as the joint author along with the human responsible for the creation of work. However, there is not much comprehensive literature available that focuses on the impact of AI being considered as a joint author. This paper aims to create a concrete foundation by emphasising such impact under the Copyright Act, 1957. Furthermore, the paper considers the stance of the US, UK and Australia in protecting AI generated works to suggest measures to the current copyright regime in India. 2023, National Institute of Science Communication and Policy Research. All rights reserved. -
IEEHR: Improved Energy Efficient Honeycomb Based Routing in MANET for Improving Network Performance and Longevity
In present scenario, efficient energy conservation has been the greatest focus in Mobile Adhoc Networks (MANETs). Typically, the energy consumption rate of dense networks is to be reduced by proper topological management. Honeycomb based model is an efficient parallel computing technique, which can manage the topological structures in a promising manner. Moreover, discovering optimal routes in MANET is the most significant task, to be considered with energy efficiency. With that motive, this paper presents a model called Improved Energy Efficient Honeycomb based Routing (IEEHR) in MANET. The model combines the Honeycomb based area coverage with Location-Aided Routing (LAR), thereby reducing the broadcasting range during the process of path finding. In addition to optimal routing, energy has to be effectively utilized in MANET, since the mobile nodes have energy constraints. When the energy is effectively consumed in a network, the network performance and the network longevity will be increased in respective manner. Here, more amount of energy is preserved during the sleeping state of the mobile nodes, which are further consumed during the process of optimal routing. The designed model has been implemented and analyzed with NS-2 Network Simulator based on the performance factors such as Energy Efficiency, Transmission Delay, Packet Delivery Ratio and Network Lifetime. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Computer Vision Based Automatic Margin Computation Model for Digital Document Images
Margin, in typography, is described as the space between the text content and the document edges and is often essential information for the consumer of the document, digital or physical. In the present age of digital disruption, it is customary to store and retrieve documents digitally and retrieve information automatically from the documents when necessary. Margin is one such non-textual information that becomes important for some business processes, and the demand for computing margins algorithmically mounts to facilitate RPA. We propose a computer vision-based text localization model, utilizing classical DIP techniques such as smoothing, thresholding, and morphological transformation to programmatically compute the top, left, right, and bottom margins within a digital document image. The proposed model has been experimented with different noise filters and structural elements of various shapes and size to finalize the bilateral filter and lines and structural elements for the removal of noises most commonly occurring due to scans. The proposed model is targeted towards text document images and not the natural scene images. Hence, the existing benchmark models developed for text localization in natural scene images have not performed with the expected accuracy. The model is validated with 485 document images of a real-time business process of a reputed TI company. The results show that 91.34 % of the document images have conferred more than 90 % IoU value which is well beyond the accuracy range determined by the company for that specific process. 2023, Crown.